3 citations · 5 across the 7 of their papers we have counts for
7 papers
Beyond Accuracy: Quantifying Pulmonary Attribution in Anatomy-Guided Chest X-Ray Classification Under Domain Shift
Abdullah Al Mamun, Md. Nasif Osman Khansur, Md Ashraful Hossen Akash +2
Deep-learning models can achieve strong chest X-ray (CXR) classification performance without establishing whether their predictions predominantly rely on pulmonary image content. T…
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…
TRIAGE: Risk-Controlled Pseudo-Label Admission for Annotation-Efficient Semi-Supervised Retinal OCT Classification
Md Ashraful Hossen Akash, Shyla Afroge, Abdullah Al Mamun +2
The advanced retinal disease diagnosing imaging modality, optical coherence tomography (OCT), encounters a lack of automation because of the high expenses for annotations performed…
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…
Mitigating hallucinations in healthcare LLMs with granular fact-checking and domain-specific adaptation
Musarrat Zeba, Abdullah Al Mamun, Kishoar Jahan Tithee +8
In healthcare, it is essential for any Large Language Model (LLM)-generated output to be reliable and accurate, particularly in cases involving decision-making and patient safety.…
Crash Severity Risk Modeling Strategies under Data Imbalance
Abdullah Al Mamun, Abyad Enan, Debbie A. Indah +3
This study investigates crash severity risk modeling strategies for work zones involving large vehicles (i.e., trucks, buses, and vans) under crash data imbalance between low-sever…
AR-GAN: Generative Adversarial Network-Based Defense Method Against Adversarial Attacks on the Traffic Sign Classification System of Autonomous Vehicles
M Sabbir Salek, Abdullah Al Mamun, Mashrur Chowdhury
This study developed a generative adversarial network (GAN)-based defense method for traffic sign classification in an autonomous vehicle (AV), referred to as the attack-resilient…