Published on in Vol 23, No 8 (2021): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26162, first published .
Patient Perceptions on Data Sharing and Applying Artificial Intelligence to Health Care Data: Cross-sectional Survey

Patient Perceptions on Data Sharing and Applying Artificial Intelligence to Health Care Data: Cross-sectional Survey

Patient Perceptions on Data Sharing and Applying Artificial Intelligence to Health Care Data: Cross-sectional Survey

Journals

  1. Saw S, Ng K. Current challenges of implementing artificial intelligence in medical imaging. Physica Medica 2022;100:12 View
  2. Schaarup J, Aggarwal R, Dalsgaard E, Norman K, Dollerup O, Ashrafian H, Witte D, Sandbæk A, Hulman A. Perception of artificial intelligence-based solutions in healthcare among people with and without diabetes: A cross-sectional survey from the health in Central Denmark cohort. Diabetes Epidemiology and Management 2023;9:100114 View
  3. Varhol R, Randall S, Boyd J, Robinson S. Australian general practitioner perceptions to sharing clinical data for secondary use: a mixed method approach. BMC Primary Care 2022;23(1) View
  4. Anderson J, McCradden M, Stephenson E. Response to Open Peer Commentaries: On Social Harms, Big Tech, and Institutional Accountability. The American Journal of Bioethics 2022;22(10):W6 View
  5. Kassam I, Ilkina D, Kemp J, Roble H, Carter-Langford A, Shen N. Patient Perspectives and Preferences for Consent in the Digital Health Context: State-of-the-art Literature Review. Journal of Medical Internet Research 2023;25:e42507 View
  6. Horsham C, Janda M, Kerr M, Soyer H, Caffery L. Consumer perceptions on privacy and confidentiality in dermatology for 3D total‐body imaging. Australasian Journal of Dermatology 2023;64(1):118 View
  7. Macri R, Roberts S. The Use of Artificial Intelligence in Clinical Care: A Values-Based Guide for Shared Decision Making. Current Oncology 2023;30(2):2178 View
  8. Caffery L, Janda M, Miller R, Abbott L, Arnold C, Caccetta T, Guitera P, Shumack S, Fernández‐Peñas P, Mar V, Soyer H. Informing a position statement on the use of artificial intelligence in dermatology in Australia. Australasian Journal of Dermatology 2023;64(1) View
  9. Kedar S, Khazanchi D. Neurology education in the era of artificial intelligence. Current Opinion in Neurology 2023;36(1):51 View
  10. Cumyn A, Ménard J, Barton A, Dault R, Lévesque F, Ethier J. Patients’ and Members of the Public’s Wishes Regarding Transparency in the Context of Secondary Use of Health Data: Scoping Review. Journal of Medical Internet Research 2023;25:e45002 View
  11. Fritsch S, Blankenheim A, Wahl A, Hetfeld P, Maassen O, Deffge S, Kunze J, Rossaint R, Riedel M, Marx G, Bickenbach J. Attitudes and perception of artificial intelligence in healthcare: A cross-sectional survey among patients. DIGITAL HEALTH 2022;8:205520762211167 View
  12. Jeyakumar T, Younus S, Zhang M, Clare M, Charow R, Karsan I, Dhalla A, Al-Mouaswas D, Scandiffio J, Aling J, Salhia M, Lalani N, Overholt S, Wiljer D. Preparing for an Artificial Intelligence–Enabled Future: Patient Perspectives on Engagement and Health Care Professional Training for Adopting Artificial Intelligence Technologies in Health Care Settings. JMIR AI 2023;2:e40973 View
  13. van der Zander Q, van der Ende - van Loon M, Janssen J, Winkens B, van der Sommen F, Masclee A, Schoon E. Artificial intelligence in (gastrointestinal) healthcare: patients’ and physicians’ perspectives. Scientific Reports 2022;12(1) View
  14. Hartzler A, Xie S, Wedgeworth P, Spice C, Lybarger K, Wood B, Duber H, Hsieh G, Singh A, Cragg K, Goomansingh S, Simons S, Wong J, Yancey-Watson A. Integrating patient voices into the extraction of social determinants of health from clinical notes: ethical considerations and recommendations. Journal of the American Medical Informatics Association 2023;30(8):1456 View
  15. Schaarup J, Aggarwal R, Dalsgaard E, Norman K, Dollerup O, Ashrafian H, Witte D, Sandbæk A, Hulman A. Perception of Artificial Intelligence in Healthcare Among People with and Without Diabetes: A Cross-Sectional Survey from the Health in Central Denmark Cohort. SSRN Electronic Journal 2022 View
  16. Nicolas J, Pitaro N, Vogel B, Mehran R. Artificial Intelligence – Advisory or Adversary?. Interventional Cardiology: Reviews, Research, Resources 2023;18 View
  17. Kunze K, Jang S, Fullerton M, Vigdorchik J, Haddad F. What’s all the chatter about?. The Bone & Joint Journal 2023;105-B(6):587 View
  18. Warner F, Tong B, McDougall J, Martin Ginis K, Rabchevsky A, Cragg J, Kramer J. Perspectives on Data Sharing in Persons With Spinal Cord Injury. Neurotrauma Reports 2023;4(1):781 View
  19. Vo V, Chen G, Aquino Y, Carter S, Do Q, Woode M. Multi-stakeholder preferences for the use of artificial intelligence in healthcare: A systematic review and thematic analysis. Social Science & Medicine 2023;338:116357 View
  20. Xu T, Ma Y, Pan T, Chen Y, Liu Y, Zhu F, Zhou Z, Chen Q. Visual Analytics of Multidimensional Oral Health Surveys: Data Mining Study. JMIR Medical Informatics 2023;11:e46275 View
  21. Ferro M, Falagario U, Barone B, Maggi M, Crocetto F, Busetto G, Giudice F, Terracciano D, Lucarelli G, Lasorsa F, Catellani M, Brescia A, Mistretta F, Luzzago S, Piccinelli M, Vartolomei M, Jereczek-Fossa B, Musi G, Montanari E, Cobelli O, Tataru O. Artificial Intelligence in the Advanced Diagnosis of Bladder Cancer-Comprehensive Literature Review and Future Advancement. Diagnostics 2023;13(13):2308 View
  22. Rockwell H, Cyphers E, Makary M, Keller E. Ethical Considerations for Artificial Intelligence in Interventional Radiology: Balancing Innovation and Patient Care. Seminars in Interventional Radiology 2023;40(03):323 View
  23. Elvas L, Ferreira J, Dias M, Rosário L. Health Data Sharing towards Knowledge Creation. Systems 2023;11(8):435 View
  24. Borondy Kitts A. Patient Perspectives on Artificial Intelligence in Radiology. Journal of the American College of Radiology 2023;20(9):863 View
  25. Ibba S, Tancredi C, Fantesini A, Cellina M, Presta R, Montanari R, Papa S, Alì M. How do patients perceive the AI-radiologists interaction? Results of a survey on 2119 responders. European Journal of Radiology 2023;165:110917 View
  26. Adus S, Macklin J, Pinto A. Exploring patient perspectives on how they can and should be engaged in the development of artificial intelligence (AI) applications in health care. BMC Health Services Research 2023;23(1) View
  27. Deisenhofer A, Barkham M, Beierl E, Schwartz B, Aafjes-van Doorn K, Beevers C, Berwian I, Blackwell S, Bockting C, Brakemeier E, Brown G, Buckman J, Castonguay L, Cusack C, Dalgleish T, de Jong K, Delgadillo J, DeRubeis R, Driessen E, Ehrenreich-May J, Fisher A, Fried E, Fritz J, Furukawa T, Gillan C, Gómez Penedo J, Hitchcock P, Hofmann S, Hollon S, Jacobson N, Karlin D, Lee C, Levinson C, Lorenzo-Luaces L, McDanal R, Moggia D, Ng M, Norris L, Patel V, Piccirillo M, Pilling S, Rubel J, Salazar-de-Pablo G, Saunders R, Schleider J, Schnurr P, Schueller S, Siegle G, Uher R, Watkins E, Webb C, Wiltsey Stirman S, Wynants L, Youn S, Zilcha-Mano S, Lutz W, Cohen Z. Implementing precision methods in personalizing psychological therapies: Barriers and possible ways forward. Behaviour Research and Therapy 2024;172:104443 View
  28. Hendricks-Sturrup R, Simmons M, Anders S, Aneni K, Wright Clayton E, Coco J, Collins B, Heitman E, Hussain S, Joshi K, Lemieux J, Lovett Novak L, Rubin D, Shanker A, Washington T, Waters G, Webb Harris J, Yin R, Wagner T, Yin Z, Malin B. Developing Ethics and Equity Principles, Terms, and Engagement Tools to Advance Health Equity and Researcher Diversity in AI and Machine Learning: Modified Delphi Approach. JMIR AI 2023;2:e52888 View
  29. Fazakarley C, Breen M, Leeson P, Thompson B, Williamson V. Experiences of using artificial intelligence in healthcare: a qualitative study of UK clinician and key stakeholder perspectives. BMJ Open 2023;13(12):e076950 View
  30. Baines R, Stevens S, Austin D, Anil K, Bradwell H, Cooper L, Maramba I, Chatterjee A, Leigh S. Patient and Public Willingness to Share Personal Health Data for Third-Party or Secondary Uses: Systematic Review. Journal of Medical Internet Research 2024;26:e50421 View
  31. Urbano V, Bartolomucci F, Azzone G. Determinants for university students’ location data sharing with public institutions during COVID-19: The Italian case. Data & Policy 2024;6 View
  32. Okenyi E, Walker L. Advantages and challenges of AI in enhancing healthcare equity. Prescriber 2024;35(1):5 View
  33. Lysen F, Wyatt S. Refusing participation: hesitations about designing responsible patient engagement with artificial intelligence in healthcare. Journal of Responsible Innovation 2024;11(1) View
  34. Aspell N, Goldsteen A, Renwick R. Dicing with data: the risks, benefits, tensions and tech of health data in the iToBoS project. Frontiers in Digital Health 2024;6 View
  35. Fazakarley C, Breen M, Thompson B, Leeson P, Williamson V. Beliefs, experiences and concerns of using artificial intelligence in healthcare: A qualitative synthesis. DIGITAL HEALTH 2024;10 View
  36. Braunack‐Mayer A, Adams C, Nettel‐Aguirre A, Fabrianesi B, Carolan L, Beilby J, Flack F. Community views on the secondary use of general practice data: Findings from a mixed‐methods study. Health Expectations 2024;27(1) View
  37. Frost E, Bosward R, Aquino Y, Braunack-Mayer A, Carter S. Facilitating public involvement in research about healthcare AI: A scoping review of empirical methods. International Journal of Medical Informatics 2024;186:105417 View

Books/Policy Documents

  1. Amofa S, Gao J, Asante-Mensah M, Haruna C, Qi X. Frontiers in Cyber Security. View
  2. Charles W, Delgado B. Blockchain in Life Sciences. View
  3. Druedahl L, Kälvemark Sporrong S. The Law and Ethics of Data Sharing in Health Sciences. View