activity
20232026
most citedEvaluating General Purpose Vision Foundation Models for Medical Image Analysis: An Experimental Study of DINOv2 on Radiology Benchmarks

8 citations · 10 across the 5 of their papers we have counts for

collaborators

6 papers

cs.HC2026

Digital Harf: A Clinically Integrated Multimodal AI System for Pervasive Arabic Speech and Language Therapy

Asif Azad, Mohammad Sadat Hossain, MD Sadik Hossain Shanto +6

Children with Autism Spectrum Disorder in Arabic-speaking countries face compounded barriers to effective speech and language therapy: a shortage of qualified specialists, limited…

cs.HC2026

Design and Evaluation of a Culturally Adapted Multimodal Virtual Agent for PTSD Screening

Cengiz Ozel, Waleed Nadeem, Samuel Potter +8

Post-traumatic stress disorder (PTSD) is highly prevalent yet chronically underreported among combat-exposed military personnel. This paper presents Molhim, a culturally adapted mu…

eess.AS2026

Harf-Speech: A Clinically Aligned Framework for Arabic Phoneme-Level Speech Assessment

Asif Azad, MD Sadik Hossain Shanto, Mohammad Sadat Hossain +6

Automated phoneme-level pronunciation assessment is vital for scalable speech therapy and language learning, yet validated tools for Arabic remain scarce. We present Harf-Speech, a…

cs.CV2025★ 1 cited

RadGame: An AI-Powered Platform for Radiology Education

Mohammed Baharoon, Siavash Raissi, John S. Jun +29

We introduce RadGame, an AI-powered gamified platform for radiology education that targets two core skills: localizing findings and generating reports. Traditional radiology traini…

cs.CV2023★ 8 cited

Evaluating General Purpose Vision Foundation Models for Medical Image Analysis: An Experimental Study of DINOv2 on Radiology Benchmarks

Mohammed Baharoon, Waseem Qureshi, Jiahong Ouyang +3

The integration of deep learning systems into healthcare has been hindered by the resource-intensive process of data annotation and the inability of these systems to generalize to…

eess.IV2023★ 1 cited

HyMNet: a Multimodal Deep Learning System for Hypertension Classification using Fundus Photographs and Cardiometabolic Risk Factors

Mohammed Baharoon, Hessa Almatar, Reema Alduhayan +6

In recent years, deep learning has shown promise in predicting hypertension (HTN) from fundus images. However, most prior research has primarily focused on analyzing a single type…