Overcoming the Data Gap for the Remote Diagnosis of Skin Cancer.
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- Record sourced from PubMed, PMID 33205141.
- Also identified by DOI 10.1016/j.patter.2020.100117 and PMC identifier 7660356.
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Abstract
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.