This paper is in the following e-collection/theme issue:

Artificial Intelligence (1371) Clinical Information and Decision Making (1407) Machine Learning (1465) mHealth for Diagnosis (60)

Published on in Vol 22, No 12 (2020): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18097, first published .
Evaluation of Four Artificial Intelligence–Assisted Self-Diagnosis Apps on Three Diagnoses: Two-Year Follow-Up Study

Evaluation of Four Artificial Intelligence–Assisted Self-Diagnosis Apps on Three Diagnoses: Two-Year Follow-Up Study

Evaluation of Four Artificial Intelligence–Assisted Self-Diagnosis Apps on Three Diagnoses: Two-Year Follow-Up Study

Authors of this article:

Aleksandar Ćirković1 Author Orcid Image
Article Authors Cited by (26) Tweetations (24) Metrics

Journals

  1. Ćirković A. Author's Reply to: Periodic Manual Algorithm Updates and Generalizability: A Developer’s Response. Comment on “Evaluation of Four Artificial Intelligence–Assisted Self-Diagnosis Apps on Three Diagnoses: Two-Year Follow-Up Study”. Journal of Medical Internet Research 2021;23(6):e29336 View
  2. Gilbert S, Fenech M, Idris A, Türk E. Periodic Manual Algorithm Updates and Generalizability: A Developer’s Response. Comment on “Evaluation of Four Artificial Intelligence–Assisted Self-Diagnosis Apps on Three Diagnoses: Two-Year Follow-Up Study”. Journal of Medical Internet Research 2021;23(6):e26514 View
  3. Deng L, Chen L, Yang T, Liu M, Li S, Jiang T. Constructing High-Fidelity Phenotype Knowledge Graphs for Infectious Diseases With a Fine-Grained Semantic Information Model: Development and Usability Study. Journal of Medical Internet Research 2021;23(6):e26892 View
  4. Kopka M, Schmieding M, Rieger T, Roesler E, Balzer F, Feufel M. Determinants of Laypersons’ Trust in Medical Decision Aids: Randomized Controlled Trial. JMIR Human Factors 2022;9(2):e35219 View
  5. Schmieding M, Kopka M, Schmidt K, Schulz-Niethammer S, Balzer F, Feufel M. Triage Accuracy of Symptom Checker Apps: 5-Year Follow-up Evaluation. Journal of Medical Internet Research 2022;24(5):e31810 View
  6. Fraser H, Cohan G, Koehler C, Anderson J, Lawrence A, Pateña J, Bacher I, Ranney M. Evaluation of Diagnostic and Triage Accuracy and Usability of a Symptom Checker in an Emergency Department: Observational Study. JMIR mHealth and uHealth 2022;10(9):e38364 View
  7. Ilicki J, Kakulapati V. Challenges in evaluating the accuracy of AI-containing digital triage systems: A systematic review. PLOS ONE 2022;17(12):e0279636 View
  8. Ollier J, Nißen M, von Wangenheim F. The Terms of “You(s)”: How the Term of Address Used by Conversational Agents Influences User Evaluations in French and German Linguaculture. Frontiers in Public Health 2022;9 View
  9. Chen P, Lu Y, Kang Y, Chang C. The Accuracy of Artificial Intelligence in the Endoscopic Diagnosis of Early Gastric Cancer: Pooled Analysis Study. Journal of Medical Internet Research 2022;24(5):e27694 View
  10. Yi-No Kang E, Chen D, Chen Y. Associations between literacy and attitudes toward artificial intelligence–assisted medical consultations: The mediating role of perceived distrust and efficiency of artificial intelligence. Computers in Human Behavior 2023;139:107529 View
  11. Kopka M, Scatturin L, Napierala H, Fürstenau D, Feufel M, Balzer F, Schmieding M. Characteristics of Users and Nonusers of Symptom Checkers in Germany: Cross-Sectional Survey Study. Journal of Medical Internet Research 2023;25:e46231 View
  12. GRAEFEN B. THE DOCTOR-PATIENT RELATIONSHIP IN THE ERA OF E-HEALTH. ESTÜDAM Halk Sağlığı Dergisi 2023;8(2):220 View
  13. Maia E, Vieira P, Praça I. Empowering Preventive Care with GECA Chatbot. Healthcare 2023;11(18):2532 View
  14. Kopka M, Feufel M, Berner E, Schmieding M. How suitable are clinical vignettes for the evaluation of symptom checker apps? A test theoretical perspective. DIGITAL HEALTH 2023;9 View
  15. Peven K, Wickham A, Wilks O, Kaplan Y, Marhol A, Ahmed S, Bamford R, Cunningham A, Prentice C, Meczner A, Fenech M, Gilbert S, Klepchukova A, Ponzo S, Zhaunova L. Assessment of a Digital Symptom Checker Tool's Accuracy in Suggesting Reproductive Health Conditions: Clinical Vignettes Study. JMIR mHealth and uHealth 2023;11:e46718 View
  16. He X, Zheng X, Ding H. Existing Barriers Faced by and Future Design Recommendations for Direct-to-Consumer Health Care Artificial Intelligence Apps: Scoping Review. Journal of Medical Internet Research 2023;25:e50342 View
  17. Hammoud M, Douglas S, Darmach M, Alawneh S, Sanyal S, Kanbour Y. Evaluating the Diagnostic Performance of Symptom Checkers: Clinical Vignette Study. JMIR AI 2024;3:e46875 View
  18. Meczner A, Cohen N, Qureshi A, Reza M, Sutaria S, Blount E, Bagyura Z, Malak T. Controlling Inputter Variability in Vignette Studies Assessing Web-Based Symptom Checkers: Evaluation of Current Practice and Recommendations for Isolated Accuracy Metrics. JMIR Formative Research 2024;8:e49907 View
  19. Nothaft F, Power B. The Most Disruptive Near-Term Use of AI in Cancer Care: Patient Empowerment Through Software Agents. AI in Precision Oncology 2024;1(5):256 View

Books/Policy Documents

  1. Yıldırım S. Computational Methods in Psychiatry. View
  2. Kaur J, Kumar P. Blockchain and IoT based Smart Healthcare Systems. View
  3. Gerke S. Digital Health Care outside of Traditional Clinical Settings. View
  4. Soms N, Azariya S. D, Saravanan A. A. Data Science in the Medical Field. View
  5. Kayyali M. Improving Entrepreneurial Processes Through Advanced AI. View