collaborators

5 papers

cs.CV2026

Infection-Reasoner: A Compact Vision-Language Model for Wound Infection Classification with Evidence-Grounded Clinical Reasoning

Palawat Busaranuvong, Reza Saadati Fard, Emmanuel Agu +4

Assessing chronic wound infection from photographs is challenging because visual appearance varies across wound etiologies, anatomical locations, and imaging conditions. Prior imag…

cs.CV2025

FT-ARM: Fine-Tuned Agentic Reflection Multimodal Language Model for Pressure Ulcer Severity Classification with Reasoning

Reza Saadati Fard, Emmanuel Agu, Palawat Busaranuvong +5

Pressure ulcers (PUs) are a serious and prevalent healthcare concern. Accurate classification of PU severity (Stages I-IV) is essential for proper treatment but remains challenging…

cs.CY2025

Stop the Nonconsensual Use of Nude Images in Research

Princessa Cintaqia, Arshia Arya, Elissa M Redmiles +3

In order to train, test, and evaluate nudity detection models, machine learning researchers typically rely on nude images scraped from the Internet. Our research finds that this co…

cs.CV2025

Explainable, Multi-modal Wound Infection Classification from Images Augmented with Generated Captions

Palawat Busaranuvong, Emmanuel Agu, Reza Saadati Fard +4

Infections in Diabetic Foot Ulcers (DFUs) can cause severe complications, including tissue death and limb amputation, highlighting the need for accurate, timely diagnosis. Previous…

cs.LG2025

Multimodal AI on Wound Images and Clinical Notes for Home Patient Referral

Reza Saadati Fard, Emmanuel Agu, Palawat Busaranuvong +4

Chronic wounds affect 8.5 million Americans, particularly the elderly and patients with diabetes. These wounds can take up to nine months to heal, making regular care essential to…