Journal
JOURNAL OF HEMATOLOGY & ONCOLOGY
Volume 13, Issue 1, Pages -Publisher
BMC
DOI: 10.1186/s13045-020-00925-y
Keywords
Severity-classification model; Acromegaly; Facial photographs; Deep learning
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Funding
- Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences [2019XK320041]
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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 similar to 3). Our developed model achieved a prediction accuracy of 90.7% on the internal test dataset and outperformed the performance of ten junior internal medicine physicians (89.0%). The prospect of applying this model to real clinical practices is promising due to its potential health economic benefits.
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