Overcoming the Data Gap for the Remote Diagnosis of Skin Cancer

Skin Cancer

Patterns (N Y). 2020 Oct 9;1(7):100117. doi: 10.1016/j.patter.2020.100117. eCollection 2020 Oct 9.


The use of AI algorithms for categorizing medical images has become very popular and critical in the diagnosis of various diseases. Current computer-aided diagnosis (CAD) systems are hugely dependent on good quality, well-annotated data captured by professional medical equipment. In many remote areas, a lack of medical equipment and medical specialists that are respectively necessary for producing good quality data and annotating data, have caused a data gap and has resulted in no possibility of

using CAD systems in those areas. Here, I point out other sources of data by previewing a recently published dataset that could help resolve this worldwide issue.