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New AI Model Predicts Mental Health Risks in Female Sex Workers

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a novel hybrid machine learning model to predict mental health risks, specifically depression, in female sex workers. This model integrates an ensemble feature selection strategy using ANOVA and mutual information with a logistic regression model optimized by Harris Hawks optimization. The system also incorporates explainable AI (XAI) methods to identify contributing factors to mental health predictions. When tested on a dataset of 3,005 individuals, the model achieved high performance metrics, including 95.78% accuracy, 95.77% F1 score, and 0.96 AUC, highlighting post-traumatic stress, client-related violence, and occupational factors as significant contributors to depression. AI

IMPACT This research demonstrates the potential of AI to provide tailored mental health support for vulnerable populations by identifying key risk factors.

RANK_REASON The cluster contains an academic paper detailing a new methodology for mental health risk prediction using machine learning.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New AI Model Predicts Mental Health Risks in Female Sex Workers

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The cluster contains an academic paper detailing a new methodology for mental health risk prediction using machine learning.
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Ahnaf Atef Choudhury, Md. Parvej Hoque Palash, Shahriar Siddique Ayon, Ramkrishna Saha, Abdullah Al Mamun ·

    Ensemble Feature Selection and Harris Hawks Optimization for Explainable Mental Health Risk Prediction in Female Sex Workers

    arXiv:2606.24047v1 Announce Type: new Abstract: One of the significant mental health issues affecting female sex workers (FSWs) is mental disorders, especially depression. Exposure to violence, stigma, and economic hardship further increases their psychological risk. Current mach…

  2. arXiv cs.LG TIER_1 English(EN) · Abdullah Al Mamun ·

    Ensemble Feature Selection and Harris Hawks Optimization for Explainable Mental Health Risk Prediction in Female Sex Workers

    One of the significant mental health issues affecting female sex workers (FSWs) is mental disorders, especially depression. Exposure to violence, stigma, and economic hardship further increases their psychological risk. Current machine learning (ML) models are typically ineffecti…

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