[Artificial intelligence and dermatology.]

The approach of artificial intelligence (AI) systems can especially support doctors who base their work on the interpretation of digital images. Despite undoubted favorable results, the validation of diagnostic algorithms in clinical practice has not yet been demonstrated. In the dermatological field, a study found the poor performance of AI systems in diagnosing skin lesions that better reflect clinical practice, that is characterized by the presence of "artifacts" such as crusts or ulcerations above the lesion, hair or pen marks, pigmentation. The algorithms also correctly classified the category of images not present in the training dataset in only 11% of cases. In almost half of the cases the images were assigned to the category of neoplasms. In clinical reality, such false positivity predictions would lead to an increase in unnecessary biopsies with a related burden of worry and anxiety for patients and their families. This confirms that the value of the data is not in their breadth but in the validity of the path that led to their use, in order not to arrive at erroneous causal inferences that could lead to poor generalizability of the results and potentially serious diagnostic errors.