Constructing an automatic diagnosis and severity-classification model for acromegaly using facial photographs by deep learning.
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ABSTRACT:
SUBMITTER: Kong Y
PROVIDER: S-EPMC7333291 | biostudies-literature | 2020 Jul
REPOSITORIES: biostudies-literature
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Constructing an automatic diagnosis and severity-classification model for acromegaly using facial photographs by deep learning.
Kong Yanguo Y Kong Xiangyi X He Cheng C Liu Changsong C Wang Liting L Su Lijuan L Gao Jun J Guo Qi Q Cheng Ran R
Journal of hematology & oncology 20200703 1
Due to acromegaly's insidious onset and slow progression, its diagnosis is usually delayed, thus causing severe complications and treatment difficulty. A convenient screening method is imperative. Based on our previous work, we herein developed a new automatic diagnosis and severity-classification model for acromegaly using facial photographs by deep learning on the data of 2148 photographs at different severity levels. Each photograph was given a score reflecting its severity (range 1~3). Our d ...[more]
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