Published on in Vol 22, No 6 (2020): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19786, first published .
A COVID-19 Risk Assessment Decision Support System for General Practitioners: Design and Development Study

A COVID-19 Risk Assessment Decision Support System for General Practitioners: Design and Development Study

A COVID-19 Risk Assessment Decision Support System for General Practitioners: Design and Development Study

Journals

  1. Mirri S, Delnevo G, Roccetti M. Is a COVID-19 Second Wave Possible in Emilia-Romagna (Italy)? Forecasting a Future Outbreak with Particulate Pollution and Machine Learning. Computation 2020;8(3):74 View
  2. Ali K, Whitebridge S, Jamal M, Alsafy M, Atkin S. Perceptions, Knowledge, and Behaviors Related to COVID-19 Among Social Media Users: Cross-Sectional Study. Journal of Medical Internet Research 2020;22(9):e19913 View
  3. Banjar H, Alkhatabi H, Alganmi N, Almouhana G. Prototype Development of an Expert System of Computerized Clinical Guidelines for COVID-19 Diagnosis and Management in Saudi Arabia. International Journal of Environmental Research and Public Health 2020;17(21):8066 View
  4. Yin Y, Chu X, Han X, Cao Y, Di H, Zhang Y, Zeng X. General practitioner trainees’ career perspectives after COVID-19: a qualitative study in China. BMC Family Practice 2021;22(1) View
  5. Wang Z, Duan Y, Jin Y, Zheng Z. Coronavirus disease 2019 (COVID-19) pandemic: how countries should build more resilient health systems for preparedness and response. Global Health Journal 2020;4(4):139 View
  6. Shanbehzadeh M, Nopour R, kazemi-arpanahi H. Determination of the Most Important Diagnostic Criteria for COVID-19: A Step forward to Design an Intelligent Clinical Decision Support System. Journal of Advances in Medical and Biomedical Research 2021;29(134):176 View
  7. Asadzadeh A, Pakkhoo S, Saeidabad M, Khezri H, Ferdousi R. Information technology in emergency management of COVID-19 outbreak. Informatics in Medicine Unlocked 2020;21:100475 View
  8. Grünebaum A, Chervenak F, McCullough L, Dudenhausen J, Bornstein E, Mackowiak P. How fever is defined in COVID-19 publications: a disturbing lack of precision. Journal of Perinatal Medicine 2021;49(3):255 View
  9. Nakamoto I, Jiang M, Zhang J, Zhuang W, Guo Y, Jin M, Huang Y, Tang K. Evaluation of the Design and Implementation of a Peer-To-Peer COVID-19 Contact Tracing Mobile App (COCOA) in Japan. JMIR mHealth and uHealth 2020;8(12):e22098 View
  10. Houlding E, Mate K, Engler K, Ortiz-Paredes D, Pomey M, Cox J, Hijal T, Lebouché B. Barriers to Use of Remote Monitoring Technologies Used to Support Patients With COVID-19: Rapid Review. JMIR mHealth and uHealth 2021;9(4):e24743 View
  11. Marin-Gomez F, Fàbregas-Escurriola M, Seguí F, Pérez E, Camps M, Peña J, Comellas A, Vidal-Alaball J, Hozbor D. Assessing the likelihood of contracting COVID-19 disease based on a predictive tree model: A retrospective cohort study. PLOS ONE 2021;16(3):e0247995 View
  12. Homeniuk R, Collins C. How COVID-19 has affected general practice consultations and income: general practitioner cross-sectional population survey evidence from Ireland. BMJ Open 2021;11(4):e044685 View
  13. Malden S, Heeney C, Bates D, Sheikh A. Utilizing health information technology in the treatment and management of patients during the COVID-19 pandemic: Lessons from international case study sites. Journal of the American Medical Informatics Association 2021;28(7):1555 View
  14. Bakin E, Stanevich O, Danilenko D, Lioznov D, Kulikov A. Fast prototyping of a local fuzzy search system for decision support and retraining of hospital staff during pandemic. Health Information Science and Systems 2021;9(1) View
  15. Abd-Alrazaq A, Hassan A, Abuelezz I, Ahmed A, Alzubaidi M, Shah U, Alhuwail D, Giannicchi A, Househ M. Overview of Technologies Implemented During the First Wave of the COVID-19 Pandemic: Scoping Review. Journal of Medical Internet Research 2021;23(9):e29136 View
  16. Khoshrounejad F, Hamednia M, Mehrjerd A, Pichaghsaz S, Jamalirad H, Sargolzaei M, Hoseini B, Aalaei S. Telehealth-Based Services During the COVID-19 Pandemic: A Systematic Review of Features and Challenges. Frontiers in Public Health 2021;9 View
  17. Lim J, Broughan J, Crowley D, O’Kelly B, Fawsitt R, Burke M, McCombe G, Lambert J, Cullen W. COVID-19’s impact on primary care and related mitigation strategies: A scoping review. European Journal of General Practice 2021;27(1):166 View
  18. Reeves J, Pageler N, Wick E, Melton G, Tan Y, Clay B, Longhurst C. The Clinical Information Systems Response to the COVID-19 Pandemic. Yearbook of Medical Informatics 2021;30(01):105 View
  19. Sukhomlinova I, Bakulin I, Kabanov M. Anti-inflammatory therapy for COVID-19: effectiveness and predictors of response. HERALD of North-Western State Medical University named after I.I. Mechnikov 2022;14(1):59 View
  20. Collins C, Petek D, Diaz E, Muñoz M. General Practice/Family Medicine Research During the Pandemic: Showing The Links to the EGPRN Research Strategy. Eurasian Journal of Family Medicine 2022;11(1):1 View
  21. Shanbehzadeh M, Kazemi-Arpanahi H, Orooji A, Mobarak S, Jelvay S. Performance evaluation of selected machine learning algorithms for COVID-19 prediction using routine clinical data: With versus Without CT scan features. Journal of Education and Health Promotion 2021;10(1):285 View
  22. Fitzsimon J, Gervais O, Lanos C. COVID-19 Assessment and Testing in Rural Communities During the Pandemic: Cross-sectional Analysis. JMIR Public Health and Surveillance 2022;8(2):e30063 View
  23. Helou R, Waltmans–den Breejen C, Severin J, Hulscher M, Verbon A, Leekha S. Use of a smartphone app to inform healthcare workers of hospital policy during a pandemic such as COVID-19: A mixed methods observational study. PLOS ONE 2022;17(1):e0262105 View
  24. Orooji A, Shanbehzadeh M, Mirbagheri E, Kazemi-Arpanahi H. Comparing artificial neural network training algorithms to predict length of stay in hospitalized patients with COVID-19. BMC Infectious Diseases 2022;22(1) View
  25. Martens M, De Wolf R, Vadendriessche K, Evens T, De Marez L. Applying contextual integrity to digital contact tracing and automated triage for hospitals during COVID-19. Technology in Society 2021;67:101748 View
  26. Smit M, Jordans C, Reinhard J, Bramer W, Verbon A, Rokx C, Calmy A. Clinical decision support systems to guide healthcare providers on HIV testing. AIDS 2022;36(8):1083 View
  27. Strong P, Shenvi A, Yu X, Papamichail K, Wynn H, Smith J. Building a Bayesian decision support system for evaluating COVID-19 countermeasure strategies. Journal of the Operational Research Society 2023;74(2):476 View
  28. Huang S, Chaudhari A, Langlotz C, Shah N, Yeung S, Lungren M. Developing medical imaging AI for emerging infectious diseases. Nature Communications 2022;13(1) View
  29. Nopour R, Shanbehzadeh M, Kazemi-Arpanahi H. Using logistic regression to develop a diagnostic model for COVID-19: A single-center study. Journal of Education and Health Promotion 2022;11(1):153 View
  30. Hasan A, Levene M, Weston D, Fromson R, Koslover N, Levene T. Monitoring COVID-19 on Social Media: Development of an End-to-End Natural Language Processing Pipeline Using a Novel Triage and Diagnosis Approach. Journal of Medical Internet Research 2022;24(2):e30397 View
  31. Chen X, Li Y, Yao L, Adeli E, Zhang Y, Wang X. Generative adversarial U-Net for domain-free few-shot medical diagnosis. Pattern Recognition Letters 2022;157:112 View
  32. Irfan I, Artama S, Wawomeo A. Determinants of the Support System and Quality of Life for Post-COVID-19 Patients. JURNAL INFO KESEHATAN 2022;20(2):143 View
  33. Moulaei K, Shanbehzadeh M, Mohammadi-Taghiabad Z, Kazemi-Arpanahi H. Comparing machine learning algorithms for predicting COVID-19 mortality. BMC Medical Informatics and Decision Making 2022;22(1) View
  34. Kashyap A, Callison-Burch C, Boland M. A deep learning method to detect opioid prescription and opioid use disorder from electronic health records. International Journal of Medical Informatics 2023;171:104979 View
  35. Xu Q, Xie W, Liao B, Hu C, Qin L, Yang Z, Xiong H, Lyu Y, Zhou Y, Luo A, Li C. Interpretability of Clinical Decision Support Systems Based on Artificial Intelligence from Technological and Medical Perspective: A Systematic Review. Journal of Healthcare Engineering 2023;2023:1 View
  36. Tan J, Tan M, Towle R, Lee J, Lei X, Liu Y, Goh R, Chee Ping F, Tan T, Ting D, Lee C, Low L. mHealth App to Facilitate Remote Care for Patients With COVID-19: Rapid Development of the DrCovid+ App. JMIR Formative Research 2023;7:e38555 View
  37. Schünke L, Mello B, da Costa C, Antunes R, Rigo S, Ramos G, Righi R, Scherer J, Donida B. A rapid review of machine learning approaches for telemedicine in the scope of COVID-19. Artificial Intelligence in Medicine 2022;129:102312 View
  38. de Sá Freire P, Kempner-Moreira F, Margherita A. Multi-Level Governance and Emergency Management: Building a Priority Assessment Matrix in the Pandemic Outbreak. Sustainability 2023;15(7):5836 View
  39. Dabbagh R, Jamal A, Bhuiyan Masud J, Titi M, Amer Y, Khayat A, Alhazmi T, Hneiny L, Baothman F, Alkubeyyer M, Khan S, Temsah M. Harnessing Machine Learning in Early COVID-19 Detection and Prognosis: A Comprehensive Systematic Review. Cureus 2023 View
  40. Liang X, Yan M, Li H, Deng Z, Lu Y, Lu P, Cai S, Li W, Fang L, Xu Z. WeChat official accounts’ posts on medication use of 251 community healthcare centers in Shanghai, China: content analysis and quality assessment. Frontiers in Medicine 2023;10 View
  41. Boateng A, Maposa D, Mokobane R, Darikwa T, Gyamfi C. Analysis of COVID-19 cases and comorbidities using machine learning algorithms: A case study of the Limpopo Province, South Africa. Scientific African 2023;21:e01840 View
  42. Schooley B, Ahmed A, Maxwell J, Feldman S. Predictors of COVID-19 From a Statewide Digital Symptom and Risk Assessment Tool: Cross-Sectional Study. Journal of Medical Internet Research 2023;25:e46026 View
  43. Ghaderzadeh M, Asadi F, Ramezan Ghorbani N, Almasi S, Taami T. Toward artificial intelligence (AI) applications in the determination of COVID-19 infection severity: considering AI as a disease control strategy in future pandemics. Iranian Journal of Blood and Cancer 2023;15(3):93 View
  44. Lv C, Guo W, Yin X, Liu L, Huang X, Li S, Zhang L. Innovative applications of artificial intelligence during the COVID-19 pandemic. Infectious Medicine 2024;3(1):100095 View
  45. Wynants L, Broers N, Platteel T, Venekamp R, Barten D, Leers M, Verheij T, Stassen P, Cals J, de Bont E. Development and validation of a risk prediction model for hospital admission in COVID-19 patients presenting to primary care. European Journal of General Practice 2024;30(1) View
  46. García-García F, Lee D, España Yandiola P, Urrutia Landa I, Martínez-Minaya J, Hayet-Otero M, Nieves Ermecheo M, Quintana J, Menéndez R, Torres A, Zalacain Jorge R. Cost-Sensitive Ordinal Classification Methods to Predict SARS-CoV-2 Pneumonia Severity. IEEE Journal of Biomedical and Health Informatics 2024;28(5):2613 View
  47. Molaei S, Moazen H, Niazkar H, Sabaei M, Johari M, Rezaianzadeh A. Application of boosted trees to the prognosis prediction of COVID‐19. Health Science Reports 2024;7(5) View
  48. Alie M, Negesse Y, Kindie K, Merawi D. Machine learning algorithms for predicting COVID-19 mortality in Ethiopia. BMC Public Health 2024;24(1) View

Books/Policy Documents

  1. Gupta R. Technologies, Artificial Intelligence and the Future of Learning Post-COVID-19. View
  2. Kesana S, Avadhanam M, Naga Malleswari T. Proceedings of International Conference on Deep Learning, Computing and Intelligence. View
  3. Vittorini P, Casano N, Sinatti G, Santini S, Balsano C. Practical Applications of Computational Biology and Bioinformatics, 16th International Conference (PACBB 2022). View