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Overcoming the Data Gap for the Remote Diagnosis of Skin Cancer.


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.

SUBMITTER: Farajnia S 

PROVIDER: S-EPMC7660356 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Overcoming the Data Gap for the Remote Diagnosis of Skin Cancer.

Farajnia Sahar S  

Patterns (New York, N.Y.) 20201009 7


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  ...[more]

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