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  2026 (3)
A pilot feasibility study of human-centered design for cirrhosis care: Development and pilot testing of SMARTLiver prototype, a FHIR-based clinical decision support system for hepatology. Sunchu, K.; Desai, A. P; Vuppalanchi, R.; and Purkayastha, S. PLOS Digital Health, 5(1): e0000969. 2026.
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Automated Logical Observation Identifiers Names and Codes mapping with biomedical natural language processing models: enabling scalable health information exchange via the Open Concept Lab. Naliyatthaliyazchayil, P.; Sangam, V. R.; Amlung, J.; Kanter, A. S; Purkayastha, S.; and Payne, J. Journal of the American Medical Informatics Association,ocag010. 2026.
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Human-Guided Agentic AI for Multimodal Clinical Prediction: Lessons from the AgentDS Healthcare Benchmark. Pulavarthy, L. P.; Muthyala, R.; Kuruvikkattil, A. V; Yin, Z.; Kudamala, R.; and Purkayastha, S. arXiv preprint arXiv:2602.19502. 2026.
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  2025 (15)
Patterns of platelet use evaluated in EHR networks of the Biologics Effectiveness and Safety Initiative, 2012–2018. Villa, C. H; Biondich, P.; Draper, N. L; Dores, G. M; Storch, E.; Chada, K.; Wong, H.; Whitaker, B.; Obidi, J.; Vossoughi, S.; and others Transfusion, 65(2): 267–276. 2025.
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DICOM LUT is a key step in medical image preprocessing towards AI generalizability. Dapamede, T.; Li, F.; Khosravi, B.; Purkayastha, S.; Trivedi, H.; and Gichoya, J. Journal of Imaging Informatics in Medicine,1–9. 2025.
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Innovating Challenges and Experiences in Emory Health AI Bias Datathon: Experience Report. Paddo, A. R.; Purkayastha, S.; Newsome, J.; Trivedi, H.; and Gichoya, J. W. Journal of Imaging Informatics in Medicine,1–10. 2025.
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Evaluating the reasoning capabilities of large language models for medical coding and hospital readmission risk stratification: zero-shot prompting approach. Naliyatthaliyazchayil, P.; Muthyala, R.; Gichoya, J. W.; and Purkayastha, S. Journal of medical Internet research, 27: e74142. 2025.
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Evaluating Vision Language Models (VLMs) for Radiology: A Comprehensive Analysis. Li, F.; Trivedi, H.; Khosravi, B.; Dapamede, T.; Chavoshi, M.; Dere, A.; Isaac, R. S.; Mansuri, A.; Newsome, J.; Purkayastha, S.; and others arXiv preprint arXiv:2504.16047. 2025.
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Role of model size and prompting strategies in extracting labels from free-text radiology reports with open-source large language models. Khosravi, B.; Dapamede, T.; Li, F.; Chisango, Z.; Bikmal, A.; Garg, S.; Owosela, B.; Khosravi, A.; Chavoshi, M.; Trivedi, H. M; and others Journal of Imaging Informatics in Medicine,1–10. 2025.
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Datawiz-IN: fostering representative innovation in health data science—outcomes from a summer research experience. Afreen, S.; Krohannon, A.; Purkayastha, S.; and Janga, S. C. BMC Medical Education, 25(1): 793. 2025.
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The Impact of Social Determinants on Cardiovascular Mortality: A Zip Code-Level Analysis in Indiana. Raju, R. T.; Telu, P.; Malepati, T.; Patel, H.; Patel, K.; and Purkayastha, S. In MEDINFO 2025—Healthcare Smart$×$ Medicine Deep, pages 1220–1224. IOS Press, 2025.
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Participatory Design for AI-Embedded Artifacts: The Case of ECEB App Design to Fostering Ownership. Purkayastha, S.; Ghimire, S.; Sunchu, K.; Bhagwat, H.; and Bucher, S. In MEDINFO 2025—Healthcare Smart$×$ Medicine Deep, pages 1307–1311. IOS Press, 2025.
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Exploring the potential of generative artificial intelligence in medical image synthesis: opportunities, challenges, and future directions. Khosravi, B.; Purkayastha, S.; Erickson, B. J; Trivedi, H. M; and Gichoya, J. W The Lancet Digital Health. 2025.
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Development of AI-integrated infrastructure with biomedical device and mobile app for neonatal vital monitoring during and in between kangaroo care sessions. Purkayastha, S.; Bhagwat, H.; Sunchu, K.; Hoilett, O.; Odari, E.; Thuo, R.; Wafula, M.; Kariuki, C.; and Bucher, S. In 2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pages 1–7, 2025. IEEE
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Mapping Extracted Free-Text Primary Diagnoses to ICD-10 and SNOMED-CT Using SciSpacy-A Performance Evaluation. Naliyatthaliyazchayil, P.; Sangam, V. R.; Muthyala, R.; and Purkayastha, S. In 2025 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI), pages 1–7, 2025. IEEE
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Leveraging digital technologies to reduce cancer disparities in low-income and middle-income countries. Gichoya, J. W; Mwavu, R.; Minja, F.; Kaonga, N.; Purkayastha, S.; and Newsome, J. The Lancet Digital Health, 7(10). 2025.
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Feature Quality and Adaptability of Medical Foundation Models: A Comparative Evaluation for Radiographic Classification and Segmentation. Li, F.; Dapamede, T.; Chavoshi, M.; Jeon, Y. S.; Khosravi, B.; Dere, A.; Brown-Mulry, B.; Isaac, R. S.; Mansuri, A.; Sanyika, C.; and others arXiv preprint arXiv:2511.09742. 2025.
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Demographic and Obstetric Factors Affecting Mental Health of Pregnant Women During COVID-19: EPDS Assessment Study. Adusumilli, S. J.; Chaitanya, S.; Pervala, N.; Quiqui, J.; and Purkayastha, S. In 2025 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI), pages 1–7, 2025. IEEE
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  2024 (19)
Theory of radiologist interaction with instant messaging decision support tools: a sequential-explanatory study. Burns, J. L.; Gichoya, J. W.; Kohli, M. D; Jones, J.; and Purkayastha, S. PLOS Digital Health, 3(2): e0000297. 2024.
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DengueNet: Dengue prediction using spatiotemporal satellite imagery for resource-limited countries. Kuo, K.; Moukheiber, D.; Ordonez, S. C.; Restrepo, D.; Paddo, A. R.; Chen, T.; Moukheiber, L.; Moukheiber, M.; Moukheiber, S.; Purkayastha, S.; and others arXiv preprint arXiv:2401.11114. 2024.
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Identifying and improving the “ground truth” of race in disparities research through improved EMR data reporting. A systematic review. Owosela, B. O; Steinberg, R. S; Leslie, S. L; Celi, L. A; Purkayastha, S.; Shiradkar, R.; Newsome, J. M; and Gichoya, J. W International Journal of Medical Informatics, 182: 105303. 2024.
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Evaluation of accessibility of open-source EHRs for visually impaired users. Moncy, M. M; Pilli, M.; Somasundaram, M.; Purkayastha, S.; and Fulton, C. R In AMIA Annual Symposium Proceedings, volume 2023, pages 1165, 2024.
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Synthetically enhanced: unveiling synthetic data's potential in medical imaging research. Khosravi, B.; Li, F.; Dapamede, T.; Rouzrokh, P.; Gamble, C. U; Trivedi, H. M; Wyles, C. C; Sellergren, A. B; Purkayastha, S.; Erickson, B. J; and others EBioMedicine, 104. 2024.
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A Skills Assessment Pathways-Based Program Assessment Approach in Multidisciplinary Graduate Health Informatics. Purkayastha, S.; Patri, A. V.; and Yerrabandi, V. In MEDINFO 2023—The Future Is Accessible, pages 1191–1195. IOS Press, 2024.
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A multi-modal satellite imagery dataset for public health analysis in colombia. Cajas, S. A; Restrepo, D.; Moukheiber, D.; Kuo, K. T.; Wu, C.; Kuo, K.; Moukheiber, D; Ordonez, S.; Restrepo, D; Paddo, A.; and others PhysioNet: Online. 2024.
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AI education for fourth-year medical students: two-year experience of a web-based, self-guided curriculum and mixed methods study. Abid, A.; Murugan, A.; Banerjee, I.; Purkayastha, S.; Trivedi, H.; and Gichoya, J. JMIR medical education, 10: e46500. 2024.
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Patterns of red blood cell utilization: Harnessing electronic health records data from the Information Standard for Blood and Transplant (ISBT) 128 system within the Biologics Effectiveness and Safety (BEST) initiative. Obidi, J.; Sridhar, G.; Dores, G. M; Whitaker, B.; Villa, C. H; Storch, E.; Chada, K.; Schilling, L. M; Natarajan, K.; Biondich, P.; and others Transfusion, 64(6): 998–1007. 2024.
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A multimodal framework for extraction and fusion of satellite images and public health data. Moukheiber, D.; Restrepo, D.; Cajas, S. A.; Montoya, M.; Celi, L. A.; Kuo, K.; López, D. M; Moukheiber, L.; Moukheiber, M.; Moukheiber, S.; and others Scientific data, 11(1): 634. 2024.
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Interpolating and Forecasting Wound Trajectory using Machine Learning Approaches. Paddo, A. R.; Shukla, S.; Steiner, S. S; Purkayastha, S.; and Sen, C. K In 2024 IEEE 37th International Symposium on Computer-Based Medical Systems (CBMS), pages 146–152, 2024. IEEE
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Utilizing ETL Processes to Enhance Healthcare Education: Migrating MIMIC-IV to OpenEMR. Kasula, M. S. K.; Sudalagunta, S. H.; Sunchu, K.; and Purkayastha, S. In 2024 IEEE 37th International Symposium on Computer-Based Medical Systems (CBMS), pages 186–191, 2024. IEEE
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Evaluating Academic Performance in Health Informatics Post-EHR Implementation. Kokkalakonda, M.; Thakur, V.; Pilli, M. P.; Purkayastha, S.; and Fulton, C. In 2024 IEEE 12th International Conference on Healthcare Informatics (ICHI), pages 739–748, 2024. IEEE
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A Scoping Review on Quantization Methods for Medical Imaging AI. Paddo, A. R.; Raju, R. T.; Gichoya, J. W.; and Purkayastha, S. In 2024 IEEE International Symposium on Biomedical Imaging (ISBI), pages 1–5, 2024. IEEE
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Measuring impact of radiologist-AI collaboration: Efficiency, accuracy, and clinical impact. Purkayastha, S.; Isaac, R.; Veldandi, A.; Saxena, R.; Singh, P.; Vaswani, P.; Krupinski, E. A; Danish, J. A; and Gichoya, J. W. In 2024 IEEE International Symposium on Biomedical Imaging (ISBI), pages 1–4, 2024. IEEE
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Personalizing Exercise Recommendations with Explanations using Multi-Armed Contextual Bandit and Reinforcement Learning. Naliyatthaliyazchayil, P.; Pemmasani, D.; Kaushal, N.; Nemati, D.; and Purkayastha, S. . 2024.
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Development and validation of the DHIS2 platform for integrating sociomedical data to study wound care outcomes. Paddo, A. R.; Kodela, S.; Timsina, L.; Mathew-Steiner, S. S; Purkayastha, S.; and Sen, C. K Plos one, 19(12): e0308553. 2024.
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Lessons Learned from OpenEMR Implementation in Graduate Health Informatics Curriculum. Sunchu, K.; Moncy, M.; Purkayastha, S.; and Fulton, C. In AMIA Annual Symposium Proceedings, volume 2024, 2024. American Medical Informatics Association
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An AI-Driven Personalized Exercise Recommendation System Using Clustering and Machine Learning Approach. Pemmasani, D.; Telu, P.; Vora, D. A. K.; Kaushal, N.; and Purkayastha, S. . 2024.
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  2023 (15)
A general-purpose ai assistant embedded in an open-source radiology information system. Purkayastha, S.; Isaac, R.; Anthony, S.; Shukla, S.; Krupinski, E. A; Danish, J. A; and Gichoya, J. W. In International conference on artificial intelligence in medicine, pages 373–377, 2023. Springer Nature Switzerland Cham
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Ethics of large language models in medicine and medical research. Li, H.; Moon, J. T; Purkayastha, S.; Celi, L. A.; Trivedi, H.; and Gichoya, J. W The Lancet Digital Health, 5(6): e333–e335. 2023.
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Medshift: automated identification of shift data for medical image dataset curation. Guo, X.; Gichoya, J. W.; Trivedi, H.; Purkayastha, S.; and Banerjee, I. IEEE journal of biomedical and health informatics, 27(8): 3936–3947. 2023.
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Hierarchical clustering and multivariate forecasting for health econometrics. Paddo, A. R.; Afreen, S.; and Purkayastha, S. In epiDAMIK 6.0: The 6th International workshop on Epidemiology meets Data Mining and Knowledge Discovery at KDD 2023, 2023.
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From seeing to knowing with artificial intelligence: a scoping review of point-of-care ultrasound in low-resource settings. Venkatayogi, N.; Gupta, M.; Gupta, A.; Nallaparaju, S.; Cheemalamarri, N.; Gilari, K.; Pathak, S.; Vishwanath, K.; Soney, C.; Bhattacharya, T.; and others Applied Sciences, 13(14): 8427. 2023.
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“Shortcuts” causing bias in radiology artificial intelligence: causes, evaluation, and mitigation. Banerjee, I.; Bhattacharjee, K.; Burns, J. L; Trivedi, H.; Purkayastha, S.; Seyyed-Kalantari, L.; Patel, B. N; Shiradkar, R.; and Gichoya, J. Journal of the American College of Radiology, 20(9): 842–851. 2023.
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Generalizability of human activity recognition machine learning models from non-Parkinson's to Parkinson's disease patients. Aswar, S.; Yerrabandi, V.; Moncy, M. M; Boda, S. R.; Jones, J.; and Purkayastha, S. In 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pages 1–4, 2023. IEEE
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Ability of artificial intelligence to identify self-reported race in chest x-ray using pixel intensity counts. Burns, J. L.; Zaiman, Z.; Vanschaik, J.; Luo, G.; Peng, L.; Price, B.; Mathias, G.; Mittal, V.; Sagane, A.; Tignanelli, C.; and others Journal of Medical Imaging, 10(6): 061106–061106. 2023.
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Foundational domains and competencies for baccalaureate health informatics education. Khairat, S.; Feldman, S. S; Rana, A.; Faysel, M.; Purkayastha, S.; Scotch, M.; and Eldredge, C. Journal of the American Medical Informatics Association, 30(10): 1599–1607. 2023.
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The telehealth dilemma—health-care deserts meet the internet’s remote regions. Kathiravelu, P.; Fonović, D.; Grbac, T. G.; Zaiman, Z.; Veiga, L.; Gichoya, J. W.; Purkayastha, S.; and Mahmoudi, B. Computer, 56(9): 39–49. 2023.
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AI pitfalls and what not to do: mitigating bias in AI. Gichoya, J. W.; Thomas, K.; Celi, L. A.; Safdar, N.; Banerjee, I.; Banja, J. D; Seyyed-Kalantari, L.; Trivedi, H.; and Purkayastha, S. The British Journal of Radiology, 96(1150): 20230023. 2023.
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The NeoRoo mobile app: Initial design and prototyping of an Android-based digital health tool to support Kangaroo Mother Care in low/middle-income countries (LMICs). Bucher, S. L.; Young, A.; Dolan, M.; Padmanaban, G. P.; Chandnani, K.; and Purkayastha, S. PLOS digital health, 2(10): e0000216. 2023.
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Healthcare Security Breaches in the United States: Insights and their Socio-Technical Implications. Moncy, M. M; Afreen, S.; and Purkayastha, S. arXiv preprint arXiv:2311.03664. 2023.
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Improving health informatics competencies using an open-source educational ehr. Purkayastha, S.; Fulton, C.; and Ratna, S. In 2023 IEEE 11th International Conference on Healthcare Informatics (ICHI), pages 645–651, 2023. IEEE
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Evaluating user acceptance of an open-source mobile app for hospital price transparency rule. Purkayastha, S.; Merine, R.; Dsouza, V.; Singh, P.; and Gichoya, J. In ECIS 2023 Research Papers, 2023.
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  2022 (16)
Margin-aware intraclass novelty identification for medical images. Guo, X.; Gichoya, J. W; Purkayastha, S.; and Banerjee, I. Journal of Medical Imaging, 9(1): 014004–014004. 2022.
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CVAD-An unsupervised image anomaly detector. Guo, X.; Gichoya, J. W.; Purkayastha, S.; and Banerjee, I. Software Impacts, 11: 100195. 2022.
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Leapfrogging medical ai in low-resource contexts using edge tensor processing unit. Sinha, P.; Gichoya, J. W; and Purkayastha, S. In 2022 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT), pages 67–70, 2022. IEEE
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LibreHealth Cost-of-Care Explorer: Mobile Application for Patient-friendly Access to Hospital Chargemasters. Merine, R.; Pinnamraju, J.; Singh, D.; Gichoya, J. W; and Purkayastha, S. In 2022 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT), pages 26–29, 2022. IEEE
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Oscars: An outlier-sensitive content-based radiography retrieval system. Guo, X.; Duan, J.; Purkayastha, S.; Trivedi, H.; Gichoya, J. W.; and Banerjee, I. In Proceedings of the 2022 International Conference on Multimedia Retrieval, pages 11–18, 2022.
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Few-Shot Transfer Learning to improve Chest X-Ray pathology detection using limited triplets. Bhimireddy, A. R.; Burns, J. L.; Purkayastha, S.; and Gichoya, J. W. arXiv preprint arXiv:2204.07824. 2022.
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Energy Efficiency of Quantized Neural Networks in Medical Imaging. Sinha, P.; Tummala, S. S.; Purkayastha, S.; and Gichoya, J. In Medical Imaging with Deep Learning, 2022.
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Development and evaluation of a natural language conversational bot for identifying appropriate clinician referral from patient narratives. Tummala, S.; Purkayastha, S.; and Jones, J. . 2022.
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AI recognition of patient race in medical imaging: a modelling study. Gichoya, J. W.; Banerjee, I.; Bhimireddy, A. R.; Burns, J. L; Celi, L. A.; Chen, L.; Correa, R.; Dullerud, N.; Ghassemi, M.; Huang, S.; and others The Lancet Digital Health, 4(6): e406–e414. 2022.
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Abstract No. 290 Comparative analysis of published chargemasters for interventional radiology procedures across the United States. Merine, R; Purkayastha, S; and Gichoya, J Journal of Vascular and Interventional Radiology, 33(6): S133. 2022.
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Multi-label medical image retrieval via learning multi-class similarity. Guo, X.; Duan, J.; Gichoya, J. W.; Trivedi, H.; Purkayastha, S.; Sharma, A.; and Banerjee, I. . 2022.
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NTD Health: an electronic medical record system for neglected tropical diseases. Ochoa, R.; Álvarez, A.; Freitas, J.; Purkayastha, S.; and Vélez, I. D Biomedica, 42(4): 602–610. 2022.
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Risks and benefits of AI-generated text summarization for expert level content in graduate health informatics. Merine, R.; and Purkayastha, S. In 2022 IEEE 10th International Conference on Healthcare Informatics (ICHI), pages 567–574, 2022. IEEE
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Using mobile virtual reality simulation to prepare for in-person helping babies breathe training: secondary analysis of a randomized controlled trial (the eHBB/mHBS trial). Ezenwa, B. N.; Umoren, R.; Fajolu, I. B.; Hippe, D. S; Bucher, S.; Purkayastha, S.; Okwako, F.; Esamai, F.; Feltner, J. B; Olawuyi, O.; and others JMIR medical education, 8(3): e37297. 2022.
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CVAD: An anomaly detector for medical images based on cascade VAE. Guo, X.; Gichoya, J. W.; Purkayastha, S.; and Banerjee, I. In Workshop on Medical Image Learning with Limited and Noisy Data, pages 187–196, 2022. Springer Nature Switzerland Cham
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Networking research innovations for telesurgery: a systematic review. Kathiravelu, P.; Benkhelifa, E.; Zaiman, Z.; Wang, M.; Correa, R.; Veiga, L.; Banerjee, I.; Trivedi, H.; Purkayastha, S.; Gichoya, J.; and others In 2022 Ninth International Conference on Software Defined Systems (SDS), pages 1–8, 2022. IEEE
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  2021 (18)
A DICOM framework for machine learning and processing pipelines against real-time radiology images. Kathiravelu, P.; Sharma, P.; Sharma, A.; Banerjee, I.; Trivedi, H.; Purkayastha, S.; Sinha, P.; Cadrin-Chenevert, A.; Safdar, N.; and Gichoya, J. W. Journal of Digital Imaging, 34(4): 1005–1013. 2021.
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Usability and Security of Different Authentication Methods for an Electronic Health Records System. Purkayastha, S.; Goyal, S.; Oluwalade, B.; Phillips, T.; Wu, H.; and Zou, X. In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (HEALTHINF), 2021.
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The Essential Care For Every Baby Digital Action Plan: Design And Usability Testing Of A Mobile Phone-Based Newborn Care Decision Support Tool In Kenya. Bucher, S. L; Rajapuri, A.; Ravindran, R.; Rukunga, J.; Horan, K.; Esamai, F.; and Purkayastha, S. 2021.
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Human Activity Recognition using Deep Learning Models on Smartphones and Smartwatches Sensor Data. Oluwalade, B.; Neela, S.; Wawira, J.; Adejumo, T.; and Purkayastha, S. In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (HEALTHINF), 2021.
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eHBB: a randomized controlled trial of virtual reality for newborn resuscitation refresher training of healthcare workers in Nigeria and Kenya. Umoren, R. A; Esamai, F.; Ezeaka, C.; Ezenwa, B.; Fajolu, I.; Nafula, M.; Makokha, F.; Hippe, D.; Feltner, J.; Patel, S.; and others Pediatrics, 147(3_MeetingAbstract): 237–238. 2021.
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Failures hiding in success for artificial intelligence in radiology. Purkayastha, S.; Trivedi, H.; and Gichoya, J. W. Journal of the American College of Radiology, 18(3): 517–519. 2021.
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Attitudes of healthcare workers in low-resource settings to mobile virtual reality simulations for newborn resuscitation training–a report from the eHBB/mHBS study. Umoren, R. A; Patel, S.; Bucher, S. L; Esamai, F.; Ezeaka, C.; Muinga, N.; Edgcombe, H.; Ezenwa, B.; Fajolu, I.; Feltner, J.; and others 2021.
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Patient-specific COVID-19 resource utilization prediction using fusion AI model. Tariq, A.; Celi, L. A.; Newsome, J. M; Purkayastha, S.; Bhatia, N. K.; Trivedi, H.; Gichoya, J. W.; and Banerjee, I. NPJ digital medicine, 4(1): 94. 2021.
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Predicting Opioid Prescriptions based on Patient Demographics in MIMIC-IV. Kodela, S.; Pinnamraju, J.; Gichoya, J. W; and Purkayastha, S. In 2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS), pages 225–230, 2021. IEEE
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Reading race: AI recognises patient's racial identity in medical images. Banerjee, I.; Bhimireddy, A. R.; Burns, J. L; Celi, L. A.; Chen, L.; Correa, R.; Dullerud, N.; Ghassemi, M.; Huang, S.; Kuo, P.; and others arXiv preprint arXiv:2107.10356. 2021.
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PLHI-MC10: A dataset of exercise activities captured through a triple synchronous medically-approved sensor. Mahajan, Y.; Bhimireddy, A.; Abid, A.; Gichoya, J. W; and Purkayastha, S. Data in Brief, 38: 107287. 2021.
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eHBB: a randomised controlled trial of virtual reality or video for neonatal resuscitation refresher training in healthcare workers in resource-scarce settings. Umoren, R.; Bucher, S.; Hippe, D. S; Ezenwa, B. N.; Fajolu, I. B.; Okwako, F. M; Feltner, J.; Nafula, M.; Musale, A.; Olawuyi, O. A; and others BMJ open, 11(8): e048506. 2021.
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Optimizing medical image classification models for edge devices. Abid, A.; Sinha, P.; Harpale, A.; Gichoya, J.; and Purkayastha, S. In International Symposium on Distributed Computing and Artificial Intelligence, pages 77–87, 2021. Springer International Publishing Cham
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Electronic Patient Records as a Substrate for Collaboration for Distributed Care in Low-Resource Contexts. Purkayastha, S. In 2021 IEEE 9th International Conference on Healthcare Informatics (ICHI), pages 289–295, 2021. IEEE
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MedShift: identifying shift data for medical dataset curation. Guo, X.; Gichoya, J. W.; Trivedi, H.; Purkayastha, S.; and Banerjee, I. arXiv preprint arXiv:2112.13885. 2021.
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Using machine learning approaches to identify exercise activities from a triple-synchronous biomedical sensor. Mahajan, Y.; Pinnamraju, J.; Burns, J. L; Gichoya, J. W; and Purkayastha, S. In International Conference on Intelligent Systems Design and Applications, pages 1216–1226, 2021. Springer International Publishing Cham
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Design and development of an integrated mHealth platform to improve kangaroo mother care in Kenya. Padmanaban, P. G.; Joshi, S. H.; Purkayastha, S.; Ekhaguere, O.; Linnes, J. C; Esamai, F.; and Bucher, S. In 2021. APHA 2021 Annual Meeting and Expo
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Towards the implementation of eco-epidemiological models for dengue in Colombia using machine learning and satellite images: Policy advocacy and open data repositories. Sebastián Osorio-Valencia, J.; Restrepo, D.; Andrés Cajas, S.; Moukheiber, D.; Escobar, B.; Sofı́a Daza, Laura; Fredy Romero, J.; Arbey Diaz, W.; Martı́nez, Luis, J.; Sundar, S.; and others Biomédica: Revista del Instituto Nacional de Salud, 41. 2021.
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  2020 (17)
The Artificial Intelligence Journal Club (# RADAIJC): a multi-institutional resident-driven web-based educational initiative. Balthazar, P.; Tajmir, S. H; Ortiz, D. A; Herse, C. C; Shea, L. A.; Seals, K. F; Cohen-Addad, D.; Purkayastha, S.; and Gichoya, J. W Academic radiology, 27(1): 136–139. 2020.
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Engagement and usability of a cognitive behavioral therapy mobile app compared with web-based cognitive behavioral therapy among college students: randomized heuristic trial. Purkayastha, S.; Addepally, S. A.; Bucher, S.; and others JMIR human factors, 7(1): e14146. 2020.
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Multi-label natural language processing to identify diagnosis and procedure codes from MIMIC-III inpatient notes. Singh, A.; Guntu, M.; Bhimireddy, A. R.; Gichoya, J. W; and Purkayastha, S. arXiv preprint arXiv:2003.07507. 2020.
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Developing and Deploying Machine Learning Pipelines against Real-Time Image Streams from the PACS. Kathiravelu, P.; Sharma, A.; Purkayastha, S.; Sinha, P.; Cadrin-Chenevert, A.; Banerjee, I.; and Gichoya, J. W. arXiv preprint arXiv:2004.07965, 10: 1–29. 2020.
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Artificial intelligence for global health: learning from a decade of digital transformation in health care. Mathur, V.; Purkayastha, S.; and Gichoya, J. W. arXiv preprint arXiv:2005.12378. 2020.
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eHBB/mHBS-DHIS2: Mobile virtual reality provider training in Helping Babies Breathe®. Umoren, R. A; Bucher, S.; Purkayastha, S.; Ezeaka, C.; Esamai, F.; Mairami, A.; Asangansi, I.; Bresnahan, B.; and Paton, C. Pediatrics, 146(1_MeetingAbstract): 290–292. 2020.
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Pre-Training Cognitive and Psychomotor Gaps in Healthcare Worker Neonatal Resuscitation Skills for Helping Babies Breathe–A Report from the eHBB/mHBS Study. Umoren, R. A; Ezeaka, C.; Esamai, F.; Kshatriya, B. A.; Avanigadda, P.; Clopp, B.; Ezenwa, B.; Fajolu, I.; Feltner, J.; Makokha, F.; and others 2020.
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Was there COVID-19 back in 2012? Challenge for AI in diagnosis with similar indications. Banerjee, I.; Sinha, P.; Purkayastha, S.; Mashhaditafreshi, N.; Tariq, A.; Jeong, J.; Trivedi, H.; and Gichoya, J. W arXiv preprint arXiv:2006.13262. 2020.
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Essential Care for Every Baby: Neonatal Clinical Decision Support Tool. Rajapuri, A. S.; Ravindran, R.; Horan, K.; Bucher, S.; and Purkayastha, S. In International Conference on Applied Human Factors and Ergonomics, pages 189–196, 2020. Springer International Publishing Cham
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Blood glucose level prediction as time-series modeling using sequence-to-sequence neural networks. Bhimireddy, A.; Sinha, P.; Oluwalade, B.; Gichoya, J. W.; and Purkayastha, S. In 2020. CEUR Workshop Proceedings
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Current clinical applications of artificial intelligence in radiology and their best supporting evidence. Tariq, A.; Purkayastha, S.; Padmanaban, G. P.; Krupinski, E.; Trivedi, H.; Banerjee, I.; and Gichoya, J. W. Journal of the American College of Radiology, 17(11): 1371–1381. 2020.
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Digital health innovations, tools, and resources to support helping babies survive programs. Bucher, S. L; Cardellichio, P.; Muinga, N.; Patterson, J. K; Thukral, A.; Deorari, A. K; Data, S.; Umoren, R.; and Purkayastha, S. Pediatrics, 146(Supplement_2): S165–S182. 2020.
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Wireless vital signs monitoring of opioid-exposed newborns during skin-to-skin care: Biomedical device innovation. Bucher, S.; Hoilett, O.; Bluhm, N.; Walters, B.; Pickering, A.; Purkayastha, S.; Linnes, J. C; Ekhaguere, O.; Ummel, J.; Padmanaban, P. G.; and others In APHA’s 2020 VIRTUAL Annual Meeting and Expo (Oct. 24-28), 2020.
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Enabling Secure and Effective Biomedical Data Sharing through Cyberinfrastructure Gateways. Goyal, S.; Purkayastha, S.; Phillips, T.; Quick, R.; and Britt, A. In Gateways 2020, 2020.
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AuthN-AuthZ: Integrated, user-friendly and privacy-preserving authentication and authorization. Phillips, T.; Yu, X.; Haakenson, B.; Goyal, S.; Zou, X.; Purkayastha, S.; and Wu, H. In 2020 Second IEEE international conference on trust, privacy and security in intelligent systems and applications (TPS-ISA), pages 189–198, 2020. IEEE
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Continuous security through integration testing in an electronic health records system. Purkayastha, S.; Goyal, S.; Phillips, T.; Wu, H.; Haakenson, B.; and Zou, X. In 2020 International Conference on Software Security and Assurance (ICSSA), pages 26–31, 2020. IEEE
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The Successful Usage of the DICOM Images Exchange System (ePACS) in the Czech Republic. Bruthans, J. Applied Clinical Informatics, 11(01): 104–111. 2020.
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  2019 (12)
Comparison of open-source electronic health record systems based on functional and user performance criteria. Purkayastha, S.; Allam, R.; Maity, P.; and Gichoya, J. W Healthcare informatics research, 25(2): 89–98. 2019.
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Evaluating the implementation of deep learning in librehealth radiology on chest x-rays. Purkayastha, S.; Buddi, S. B.; Nuthakki, S.; Yadav, B.; and Gichoya, J. W In Science and Information Conference, pages 648–657, 2019. Springer International Publishing Cham
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Critical Components of Formative Assessment in Process-Oriented Guided Inquiry Learning for Online Labs. Purkayastha, S.; Surapaneni, A. K; Maity, P.; Rajapuri, A. S; and Gichoya, J. W Electronic Journal of E-learning, 17(2): 79–92. 2019.
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Identification of patients in need of advanced care for depression using data extracted from a statewide health information exchange: a machine learning approach. Kasthurirathne, S. N; Biondich, P. G; Grannis, S. J; Purkayastha, S.; Vest, J. R; and Jones, J. F Journal of medical Internet research, 21(7): e13809. 2019.
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Full training versus fine tuning for radiology images concept detection task for the ImageCLEF 2019 challenge. Sinha, P.; Purkayastha, S.; and Gichoya, J. . 2019.
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The development and usability testing of a decision support mobile app for the Essential Care for Every Baby (ECEB) program. Nuthakki, S.; Bucher, S.; and Purkayastha, S. In International Conference on Human-Computer Interaction, pages 259–263, 2019. Springer International Publishing Cham
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Learning gains of process oriented guided inquiry learning in an online course setting. Purkayastha, S.; Guntu, M.; Ravindran, R.; and Surapaneni, A. K. In 2019. Academic Conferences International Limited
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Natural language processing of MIMIC-III clinical notes for identifying diagnosis and procedures with neural networks. Nuthakki, S.; Neela, S.; Gichoya, J. W; and Purkayastha, S. arXiv preprint arXiv:1912.12397. 2019.
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Trends in RED Blood CELL Transfusions within the Biologics Effectiveness and Safety (BEST) Initiative Network, 2012-2018. Obidi, J.; Villa, C.; Storch, E.; Whitaker, B.; Chada, K.; Williams, A.; Fowler, S.; Schilling, L. M; Kahn, M. G; Edlavitch, S. A; and others . 2019.
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Development and Implementation of a Dashboard for Diabetes Care Management in OpenMRS. Teja Yandrapalli, B.; Jones, J.; and Purkayastha, S. arXiv e-prints,arXiv–1910. 2019.
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Development and implementation of a dashboard for diabetes care management in OpenMRS. Yandrapalli, B. T.; Jones, J.; and Purkayastha, S. arXiv preprint arXiv:1910.11437. 2019.
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FW-HTF-RM: Measuring learning gains in man-machine assemblage when augmenting radiology work with artificial intelligence. Purkayastha, S. NSF Award Number 1928481. Directorate for Engineering, 19(1928481): 28481. 2019.
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  2018 (9)
Phronesis of AI in radiology: Superhuman meets natural stupidity. Gichoya, J. W; Nuthakki, S.; Maity, P. G; and Purkayastha, S. arXiv preprint arXiv:1803.11244. 2018.
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A platform for innovation and standards evaluation: a case study from the OpenMRS open-source radiology information system. Gichoya, J. W; Kohli, M.; Ivange, L.; Schmidt, T. S; and Purkayastha, S. Journal of digital imaging, 31(3): 361–370. 2018.
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Overcoming the maternal care crisis: how can lessons learnt in global health informatics address US maternal health outcomes?. Kasthurirathne, S. N; Mamlin, B. W; Purkayastha, S.; and Cullen, T. In AMIA Annual Symposium Proceedings, volume 2017, pages 1034, 2018.
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Improving “Desktop medicine” efficiency using Guided Inquiry Learning in an Electronic Health Records System. Purkayastha, S.; Naliyatthaliyazchayil, P. R. M.; Surapaneni, A. K.; Kowkutla, A.; and Maity, P. . 2018.
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Implementing Guided Inquiry Learning and Measuring Engagement Using an Electronic Health Record System in an Online Setting. Purkayastha, S.; Surapaneni, A. K.; and Maity, P. In 2018. Academic Conferences International Limited
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Development of an innovative mobile phone-based newborn care training application. Bucher, S.; Meyers, E.; Kshatriya, B. S. A.; Avanigadda, P. C.; and Purkayastha, S. In International Conference on Innovations in Bio-Inspired Computing and Applications, pages 361–374, 2018. Springer International Publishing Cham
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Finding the Best EHR Training Dataset: A Cross-over Trial. Jones, J. F; Fatima, R.; Purkayastha, S.; Kulanthaivel, A.; and Zhang, E. In AMIA, 2018.
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Implementing Guided Inquiry Learning and Measuring Engagement using an Electronic Health Record System in an Online Setting. Maity, P.; and Purkayastha, S. Assessment. 2018.
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A Platform for Innovation and Standards Evaluation: a Case Study from the OpenMRS Open-Source Radiology Information System. Kohli, M.; Ivange, L.; Schmidt, T. S; and Purkayastha, S. Journal of Digital Imaging (Online), 31(3). 2018.
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  2017 (7)
Implementation of a single sign-on system between practice, research and learning systems. Purkayastha, S.; Gichoya, J. W; and Addepally, A. S. Applied clinical informatics, 26(01): 306–312. 2017.
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Conversion of JPG image into DICOM image format with one click tagging. Oladiran, O.; Gichoya, J.; and Purkayastha, S. In International Conference on Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management, pages 61–70, 2017. Springer International Publishing Cham
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Mobile-application based cognitive behavior therapy (CBT) for identifying and managing depression and anxiety. Addepally, S. A.; and Purkayastha, S. In International Conference on Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management, pages 3–12, 2017. Springer International Publishing Cham
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Using cognitive fit theory to evaluate patient understanding of medical images. Gichoya, J. W.; Alarifi, M.; Bhaduri, R.; Tahir, B.; and Purkayastha, S. In 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pages 2430–2433, 2017. IEEE
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Know thy eHealth user: Development of biopsychosocial personas from a study of older adults with heart failure. Holden, R. J; Kulanthaivel, A.; Purkayastha, S.; Goggins, K. M; and Kripalani, S. International journal of medical informatics, 108: 158–167. 2017.
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Comparative performance analysis of different fingerprint biometric scanners for patient matching. Kasiiti, N.; Wawira, J.; Purkayastha, S.; and Were, M. C . 2017.
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Implementing clinical practice guidelines for chronic obstructive pulmonary disease in an EHR system. Walker, M.; Ge, W.; Gichoya, J. W; and Purkayastha, S. In 2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT), pages 148–151, 2017. IEEE
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  2015 (2)
From dyadic ties to information infrastructures: care-coordination between patients, providers, students and researchers. Purkayastha, S.; Price, A; Biswas, R; Ganesh, A. J.; and Otero, P Yearbook of medical informatics, 24(01): 68–74. 2015.
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The Genus of Information Infrastructures: Architecture, Governance & Praxis. Purkayastha, S. Ph.D. Thesis, Norwegian University of Science and Technology, Trondheim, Norway, 2015.
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  2014 (1)
OpenScrum: Scrum methodology to improve shared understanding in an open-source community. Purkayastha, S. . 2014.
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  2013 (4)
A Post-development Perspective on mHealth–An Implementation Initiative in Malawi. Purkayastha, S.; Manda, T. D.; and Sanner, T. A. In 2013 46th Hawaii International Conference on System Sciences, pages 4217–4225, 2013. IEEE
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2052: A global forecast for the next forty years. Purkayastha, S. International Journal of User-Driven Healthcare (IJUDH), 3(1): 88–89. 2013.
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Big data analytics for developing countries–using the cloud for operational BI in health. Purkayastha, S.; and Braa, J. The Electronic Journal of Information Systems in Developing Countries, 59(1): 1–17. 2013.
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Overview, not Overwhelm: Framing Operational BI Tools using Organizational Capabilities. Purkayastha, S.; and Braa, J. . 2013.
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  2012 (4)
Design and Implementation of Mobile-Based Technology in Strengthening Health Information System: Aligning mHealth Solutions to Infrastructures. Purkayastha, S. Mobile Computing Techniques in Emerging Markets: Systems, Applications and Services,158. 2012.
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Dyscover—An Orton-Gillingham approach inspired multi-sensory learning application for dyslexic children. Purkayastha, S.; Nehete, N.; and Purkayastha, J. In 2012 World Congress on Information and Communication Technologies, pages 685–690, 2012. IEEE
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Hixen: An integration engine for multi-vocabulary health information using rest & semantic metadata mapping. Purkayastha, S. In 2012 World Congress on Information and Communication Technologies, pages 679–684, 2012. IEEE
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The Mobile is Part of a Whole: Lessons from an mHealth Implementation in Malawi. Manda, T. D.; Sanner, T. A; Purkayastha, S.; and Nyirenda, E. Technical Report 2012.
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  2011 (1)
Towards a contextual insecurity framework: How contextual development leads to security problems in information systems. Purkayastha, S. In Proceedings of IRIS 2011, pages 654–666. Turku Centre for Computer Science, 2011.
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  2010 (2)
Sustainable mobile information infrastructures in low resource settings. Braa, K.; and Purkayastha, S. In Information Technology in Health Care: Socio-Technical Approaches 2010, pages 127–132. IOS Press, 2010.
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Exploring the potential and challenges of using mobile based technology in strengthening health information systems: Experiences from a pilot study. Mukherjee, A.; Purkayastha, S.; and Sahay, S. In AMCIS 2010 Proceedings, pages Paper–263, 2010.
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  undefined (3)
Was there COVID-19 back in 2012? Challenge for AI in Diagnosis with Similar Indications. arXiv 2020. Banerjee, I; Sinha, P; Purkayastha, S; Mashhaditafreshi, N; Tariq, A; Jeong, J.; Trivedi, H; and Gichoya, J. arXiv preprint arXiv:2006.13262. .
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Using HL7 FHIR to Integrate Structured Reporting Reports into an Open Source Medical Records System. Genereaux, B.; Karunarathne, M.; Purkayastha, S.; and Kahn, C. E . .
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Patient-specific COVID-19 resource utilization prediction using fusion AI model. Purkayastha, S. npj Digital Medicine. .
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