Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44065, first published .
Integrating Clinical Decision Support Into Electronic Health Record Systems Using a Novel Platform (EvidencePoint): Developmental Study

Integrating Clinical Decision Support Into Electronic Health Record Systems Using a Novel Platform (EvidencePoint): Developmental Study

Integrating Clinical Decision Support Into Electronic Health Record Systems Using a Novel Platform (EvidencePoint): Developmental Study

Journals

  1. Yakob N, Laliberté S, Doyon-Poulin P, Jouvet P, Noumeir R. Data Representation Structure to Support Clinical Decision-Making in the Pediatric Intensive Care Unit: Interview Study and Preliminary Decision Support Interface Design. JMIR Formative Research 2024;8:e49497 View
  2. Wang J, Ji M, Han Y, Wu Y. Development and Usability Testing of a Mobile App–Based Clinical Decision Support System for Delirium: Randomized Crossover Trial. JMIR Aging 2024;7:e51264 View
  3. Tsaftaridis N, Goldin M, Spyropoulos A. System-Wide Thromboprophylaxis Interventions for Hospitalized Patients at Risk of Venous Thromboembolism: Focus on Cross-Platform Clinical Decision Support. Journal of Clinical Medicine 2024;13(7):2133 View
  4. Goldin M, Tsaftaridis N, Koulas I, Solomon J, Qiu M, Leung T, Smith K, Ochani K, McGinn T, Spyropoulos A. Universal clinical decision support tool for thromboprophylaxis in hospitalized COVID-19 patients: post hoc analysis of the IMPROVE-DD cluster randomized trial. Journal of Thrombosis and Haemostasis 2024;22(11):3172 View
  5. Woller S, Stevens S, Bledsoe J, Hellewell J, Kraft A, Butler A, Fazili M, Lloyd J, Christensen P, Peltan I, Barnes G, Horne B. Methods of a cluster-randomized, type II hybrid implementation effectiveness trial to prospectively assess extended-duration thromboprophylaxis for at-risk medical patients being discharged to prevent hospital-associated venous thromboembolism. Research and Practice in Thrombosis and Haemostasis 2024;8(6):102549 View
  6. Frenkel A, Rendon A, Chavez-Lencinas C, Gomez De la Torre J, MacDermott J, Gross C, Allman S, Lundblad S, Zavala I, Gross D, Siegel J, Choi S, Hueda-Zavaleta M. Internal Validation of a Machine Learning-Based CDSS for Antimicrobial Stewardship. Life 2025;15(7):1123 View
  7. Sawaied I, Samson A, Golan E. Perceived risk of gastric cancer associated with long-term use of proton pump inhibitors: Bridging the gap. World Journal of Clinical Oncology 2025;16(7) View
  8. Rego C, Hailye H, Montague E. Evaluating Levels of Automation in Primary Care Technologies: Identifying Gaps and Opportunities to Enhance Patient and Physician Experiences. Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care 2025;14(1):49 View
  9. Lin S, Groenwold R, Mehta H, Kim J, Segal J. Addressing Missingness in Predictive Models That Use Electronic Health Record Data. Annals of Internal Medicine 2025;178(10):1451 View
  10. Xie X, Yu M, Xu R, Liu Y, Zhang J. From Ulcer to Amputation: A Systematic Review of Prognostic Models for Diabetic Foot Ulcer Amputation. Risk Management and Healthcare Policy 2025;Volume 18:3099 View
  11. Sahu A, Mathur S, Takaoka H, Ota J, Meinel F, Böttcher B, Magnin B, Jajodia A, Jensen C. Transforming CT imaging with deep learning: Noise reduction, artifact management, and clinical applications – A comprehensive review. European Journal of Radiology Artificial Intelligence 2025;4:100042 View

Books/Policy Documents

  1. Gahane S, Khode P, Verma P. ICT Systems and Sustainability. View
  2. Gahane S, Khode P, Sharma D, Anawade P. ICT Systems and Sustainability. View
  3. Gahane S, Verma P. Integration of Artificial Intelligence in IoT: Opportunities and Challenges. View

Conference Proceedings

  1. Rahmadani F, Simsekler M. 2024 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD). A Path Towards Human-AI Decision-Making in Sepsis Care through Human-Centered Systems-Based Design Approach View