In a recent review published in the Life Journal, a group of authors reviewed image-processing techniques in machine learning (ML) for skin cancer detection using clinical images, evaluating their ...

In this study, researchers used machine learning and combination theory to distil 22 clinical features down to the seven most important that predict if a skin lesion might be suspicious or not.

LUGANO, 30 September, 2021 – A new study has found that a direct-to-consumer machine learning model for detecting skin cancers incorrectly classified rare and aggressive cancers as low-risk.1 ...

New technology using AI to tell the difference between harmless moles and dangerous melanomas has hit the market. Created by FotoFinder Systems, Moleanalyzer pro is a portal that lets physicians ...

A new dual-modal, non-invasive detection technique could make it easier—and faster—to differentiate between melanoma skin cancer and benign lesions. The combination of optical coherence ...

It's still in the investigative phase. A clinical trial, published almost 5 years ago, demonstrated a sensitivity of 90%-99% and a specificity of 24%-66% for skin cancer.

The German-made machine and others like it use global databases of skin cancer photos to improve analysis; as the database grows, the AI learns to become even better at identifying skin cancers.

Hospitals Are Getting IBM's Skin Cancer Detection System The machine learning system is already better than a doctor's naked eye at identifying cancers.