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

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

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