Network architecture of DeepGAM.

Network architecture of DeepGAM.

<p>( <b>a</b>) Each feature passes through a Straight-Through Estimator (STE), which learns to select relevant features during training. The selected feature <i>z</i><sub><i>j</i></sub> is then fed into a 3-layer neural network <i>f</i&g...

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Bibliographic Details
Main Author:	Chiyoung Lee (11782395) (author)
Other Authors:	Yeri Kim (21539075) (author), Seoyoung Kim (2603596) (author), Mary Whooley (6090683) (author), Heewon Kim (7498565) (author)
Published:	2025
Subjects:	Neuroscience Mental Health Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified surpassed traditional methods study &# 8217 predicting depression compared estimating depression status ste demonstrated accurate personal medical data interpretable function visualizations soul study objective function diagnosing depression depression diagnosis interpretable performance sectional data public datasets neural network network architecture negative impacts input component individual effects individual components increasing attention highest auc black boxes baseline cross
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