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

Mobile Apps for Dermatology and Prevention (23) Artificial Intelligence (2129) Clinical Information and Decision Making (1915) Decision Support for Health Professionals (1539) Machine Learning (2076)

Published on in Vol 6 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45529, first published .
Analyzing the Predictability of an Artificial Intelligence App (Tibot) in the Diagnosis of Dermatological Conditions: A Cross-sectional Study

Analyzing the Predictability of an Artificial Intelligence App (Tibot) in the Diagnosis of Dermatological Conditions: A Cross-sectional Study

Analyzing the Predictability of an Artificial Intelligence App (Tibot) in the Diagnosis of Dermatological Conditions: A Cross-sectional Study

Authors of this article:

Shiva Shankar Marri1 Author Orcid Image ;   Arun C Inamadar1 Author Orcid Image ;   Ajit B Janagond1 Author Orcid Image ;   Warood Albadri1 Author Orcid Image
Article Authors Cited by (11) Tweetations (4) Metrics

Journals

  1. Sengupta D. Artificial Intelligence in Diagnostic Dermatology: Challenges and the Way Forward. Indian Dermatology Online Journal 2023;14(6):782 View
  2. Novykov V, Bilson C, Gepp A, Harris G, Vanstone B. Deep learning applications in investment portfolio management: a systematic literature review. Journal of Accounting Literature 2025;47(2):245 View
  3. Marri S, Albadri W, Hyder M, Janagond A, Inamadar A. Efficacy of an Artificial Intelligence App (Aysa) in Dermatological Diagnosis: Cross-Sectional Analysis. JMIR Dermatology 2024;7:e48811 View
  4. Khalid U, Chen L, Khan A, Chen B, Mehmood F, Yasir M. A smart facial acne disease monitoring for automate severity assessment using AI-enabled cloud-based internet of things. Discover Computing 2025;28(1) View
  5. Ribeiro Silva Fernandes T, Teles A, Renan Neves Fernandes J, Daniel Batista Lima L, Lima Sousa D, de Castro Soares R, Silva Teixeira S. External Validation of AI Models for Skin Diseases: A Systematic Review. IEEE Access 2025;13:114411 View
  6. Soliman S, Korany M, Tawfik N. Precision revealed: diagnostic performance by consumer artificial intelligence powered app in recognizing skin conditions in primary care settings. Journal of the Egyptian Women's Dermatologic Society 2025;22(3):279 View
  7. Tekchandani N, Mukherjee A, Poonthottam N, Boussios S. Comparative Analysis of Large Language Models in Dermatological Diagnosis: An Evaluation of Diagnostic Accuracy. Cureus 2025 View
  8. Hubail M, Abdel Khabir A, Al Emam D, Fouad S. Artificial Intelligence in Dermatology: Assessing Predictability in Clinical Diagnosis. The Open Dermatology Journal 2025;19(1) View
  9. Korabelnikov D, Lamotkin A. Artificial intelligence in dermatology: a comparative analysis of computer vision programs based on machine learning models. FARMAKOEKONOMIKA. Modern Pharmacoeconomics and Pharmacoepidemiology 2025 View

Books/Policy Documents

  1. Salem E, AlEdani E. Applications of Artificial Intelligence in Common Dermatological Diseases. View

Conference Proceedings

  1. Kumari S, Umrao S, Kushwaha D. 2024 2nd International Conference on Disruptive Technologies (ICDT). Decoding the Skin with AI: A Review of Cutting-Edge Technologies and Applications* View