From the 1 of 15 linked papers with an AI index.
15 papers
Beyond the Leaderboard: Design Lessons for Trustworthy Multimodal VQA
Sushant Gautam, Vajira Thambawita, Michael A. Riegler +2
The paper studies how design choices affect the reliability and interpretability of multimodal visual question answering systems for gastrointestinal endoscopy, finding that struct…
Ask Before You Diagnose: Safe-Psych, a Sequential Evaluation Benchmark for LLMs in Psychiatry
Oriana Presacan, Andreea Grama, Larisa IriminÄ +6
Large language models (LLMs) are increasingly used for decision support in healthcare, but clinical evidence is often incomplete or evolving. When the available information is insu…
Sampling Matters: The Effect of ECG Frequency on Deep Learning-Based Atrial Fibrillation Detection
Arjan Mahmuod, Adrian Rod Hammerstad, Muzaffar Yousef +5
Deep learning models for atrial fibrillation (AF) detection are increasingly trained on heterogeneous electrocardiogram (ECG) datasets with varying sampling frequencies, yet the sp…
Knowledge-Guided Retrieval-Augmented Generation for Zero-Shot Psychiatric Data: Privacy Preserving Synthetic Data Generation
Adam Jakobsen, Sushant Gautam, Hugo Lewi Hammer +4
AI systems in healthcare research have shown potential to increase patient throughput and assist clinicians, yet progress is constrained by limited access to real patient data. To…
Synthetic Cardiac MRI Image Generation using Deep Generative Models
Ishan Kumarasinghe, Dasuni Kawya, Madhura Edirisooriya +3
Synthetic cardiac MRI (CMRI) generation has emerged as a promising strategy to overcome the scarcity of annotated medical imaging data. Recent advances in GANs, VAEs, diffusion pro…
Balancing Fidelity, Utility, and Privacy in Synthetic Cardiac MRI Generation: A Comparative Study
Madhura Edirisooriya, Dasuni Kawya, Ishan Kumarasinghe +5
Deep learning in cardiac MRI (CMR) is fundamentally constrained by both data scarcity and privacy regulations. This study systematically benchmarks three generative architectures:…