collaborators

6 papers

cs.LG2026

SAGE: Stability-Aware Graph-Based Ensemble Feature Selection for Explainable Postpartum Depression Risk Prediction

Md. Rokon Islam Emon, Syed Shariar Alam Shuvo, Shahriar Siddique Ayon +2

Postpartum depression (PPD) poses a major burden on maternal and child health, especially in low- and middle-income countries where prevalence exceeds 19%. Despite advancements in…

cs.CL2026

SDoH-Aware Narrative Anchoring Bias in Medical LLMs for Trustworthy Clinical Decision Support

Ahnaf Atef Choudhury, Ramkrishna Saha

Medical large language models are often judged by how many clinical questions they answer correctly. That view is useful, but it misses a practical risk. A model may know the right…

cs.AI2026

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

Ahnaf Atef Choudhury, Md. Parvej Hoque Palash, Shahriar Siddique Ayon +2

One of the significant mental health issues affecting female sex workers (FSWs) is mental disorders, especially depression. Exposure to violence, stigma, and economic hardship furt…

cs.LG2026

Explainable AI for Mental Health Prediction in Drug-Affected Populations with Dragonfly Algorithm and GAN Oversampling

Ahnaf Atef Choudhury, Shahriar Siddique Ayon, Md. Ebrahim Hossain +1

Mental illnesses among drug users are an increasing international issue, particularly in regions where early detection cannot be easily undertaken. The current literature tends to…

cs.CL2026

Towards Intelligent Legal Document Analysis: CNN-Driven Classification of Case Law Texts

Moinul Hossain, Sourav Rabi Das, Zikrul Shariar Ayon +4

Legal practitioners and judicial institutions face an ever-growing volume of case-law documents characterised by formalised language, lengthy sentence structures, and highly specia…

cs.LG2026

Hybrid Approach for Driver Behavior Analysis with Machine Learning, Feature Optimization, and Explainable AI

Mehedi Hasan Shuvo, Md. Raihan Tapader, Nur Mohammad Tamjid +3

Progressive driver behavior analytics is crucial for improving road safety and mitigating the issues caused by aggressive or inattentive driving. Previous studies have employed mac…