AI in Medicine — Importance of Prospective Study; Disparity between Retrospective and Prospective Result

  1. Assessment of Deep Neural Networks for the Diagnosis of Benign and Malignant Skin Neoplasms in Comparison with Dermatologists: A Retrospective Validation Study. PLOS Medicine, 2020
  2. Performance of a deep neural network in teledermatology: a single‐center prospective diagnostic study. J Eur Acad Dermatol Venereol. 2020
  3. Keratinocytic Skin Cancer Detection on the Face using Region-based Convolutional Neural Network. JAMA Dermatol. 2019
  4. Seems to be low, but is it really poor? : Need for Cohort and Comparative studies to Clarify Performance of Deep Neural Networks. J Invest Dermatol. 2020
  5. Multiclass Artificial Intelligence in Dermatology: Progress but Still Room for Improvement. J Invest Dermatol. 2020
  6. Augment Intelligence Dermatology : Deep Neural Networks Empower Medical Professionals in Diagnosing Skin Cancer and Predicting Treatment Options for 134 Skin Disorders. J Invest Dermatol. 2020
  7. Interpretation of the Outputs of Deep Learning Model trained with Skin Cancer Dataset. J Invest Dermatol. 2018
  8. Automated Dermatological Diagnosis: Hype or Reality? J Invest Dermatol. 2018
  9. Classification of the Clinical Images for Benign and Malignant Cutaneous Tumors Using a Deep Learning Algorithm. J Invest Dermatol. 2018
  10. Augmenting the Accuracy of Trainee Doctors in Diagnosing Skin Lesions Suspected of Skin Neoplasms in a Real-World Setting: A Prospective Controlled Before and After Study. PLOS One, 2022
  11. Evaluation of Artificial Intelligence-assisted Diagnosis of Skin Neoplasms — a single-center, paralleled, unmasked, randomized controlled trial. J Invest Dermatol. 2022

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