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20242026
most citedTrustworthy AI in Digital Health: A Comprehensive Review of Robustness and Explainability

2 citations · 2 across the 2 of their papers we have counts for

collaborators

8 papers

cs.AI20262 cited

Trustworthy AI in Digital Health: A Comprehensive Review of Robustness and Explainability

Abdullah Mamun, Shovito Barua Soumma, Hassan Ghasemzadeh

Ensuring trust in AI systems is essential for the safe and ethical integration of machine learning systems into high-stakes domains such as digital health. Key dimensions, includin…

eess.SP2026

Comprehensive Dataset and Signal Processing Framework for Phonocardiogram-Based Heart Rate and Blood Pressure Estimation

Abdul Ahad Mamun, Utsab Saha, Md Hasibul Hasan +2

Cardiovascular diseases (CVDs) represent significant global health challenges today, necessitating regular and reliable monitoring to enable early intervention. Phonocardiogram (PC…

cs.LG2026

Use of What-if Scenarios to Help Explain Artificial Intelligence Models for Neonatal Health

Abdullah Mamun, Lawrence D. Devoe, Mark I. Evans +3

Early detection of intrapartum risks enables timely interventions to prevent or mitigate adverse labor outcomes such as cerebral palsy. However, accurate automated systems to suppo…

cs.LG2025

LLM-Powered Prediction of Hyperglycemia and Discovery of Behavioral Treatment Pathways from Wearables and Diet

Abdullah Mamun, Asiful Arefeen, Susan B. Racette +4

Postprandial hyperglycemia, marked by the blood glucose level exceeding the normal range after consuming a meal, is a critical indicator of progression toward type 2 diabetes in pe…

cs.LG2025

Enhancing Metabolic Syndrome Prediction with Hybrid Data Balancing and Counterfactuals

Sanyam Paresh Shah, Abdullah Mamun, Shovito Barua Soumma +1

Metabolic Syndrome (MetS) is a cluster of interrelated risk factors that significantly increases the risk of cardiovascular diseases and type 2 diabetes. Despite its global prevale…

cs.LG2025

Freezing of Gait Detection Using Gramian Angular Fields and Federated Learning from Wearable Sensors

Shovito Barua Soumma, S M Raihanul Alam, Rudmila Rahman +4

Freezing of gait (FOG) is a debilitating symptom of Parkinson's disease that impairs mobility and safety by increasing the risk of falls. An effective FOG detection system must be…