HIGHLIGHTS
- who: Unknown from the (UNIVERSITY) have published the Article: Fairness in Mobile Phone-Based Mental Health Assessment Algorithms: Exploratory Study, in the Journal: (JOURNAL)
- what: Motivated by previous work on algorithmic fairness (see the Algorithmic Fairness section), this study attempted to mitigate the discriminatory impact of gender on mental health prediction algorithms. After passing a preprocessing and classification process, the study showed that automated ML algorithms using phone-based features achieved up to 80% accuracy in automatically classifying the mental health level (above or below the mean) of an individual . Using the abovementioned data, the . . .
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