19 citations · 59 across the 19 of their papers we have counts for
21 papers
Beyond the Leaderboard: Design Lessons for Trustworthy Multimodal VQA
Sushant Gautam, Vajira Thambawita, Michael A. Riegler +2
Healthcare multimodal AI must combine visual and textual evidence while remaining reliable and interpretable. Using MediaEval Medico 2025 as a retrospective GI endoscopy case study…
Ask Before You Diagnose: Safe-Psych, a Sequential Evaluation Benchmark for LLMs in Psychiatry
Oriana Presacan, Andreea Grama, Larisa Irimină +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:…
VideoHEDGE: Entropy-Based Hallucination Detection for Video-VLMs via Semantic Clustering and Spatiotemporal Perturbations
Sushant Gautam, Cise Midoglu, Vajira Thambawita +2
Hallucinations in video-capable vision-language models (Video-VLMs) remain frequent and high-confidence, while existing uncertainty metrics often fail to align with correctness. We…
Medical Imaging AI Competitions Lack Fairness
Annika Reinke, Evangelia Christodoulou, Sthuthi Sadananda +34
Benchmarking competitions are central to the development of artificial intelligence (AI) in medical imaging, defining performance standards and shaping methodological progress. How…
A Comparative Study of Decoding Strategies in Medical Text Generation
Oriana Presacan, Alireza Nik, Vajira Thambawita +2
Large Language Models (LLMs) rely on various decoding strategies to generate text, and these choices can significantly affect output quality. In healthcare, where accuracy is criti…
AICRN: Attention-Integrated Convolutional Residual Network for Interpretable Electrocardiogram Analysis
J. M. I. H. Jayakody, A. M. H. H. Alahakoon, C. R. M. Perera +4
The paradigm of electrocardiogram (ECG) analysis has evolved into real-time digital analysis, facilitated by artificial intelligence (AI) and machine learning (ML), which has impro…
Inductive transfer learning from regression to classification in ECG analysis
Ridma Jayasundara, Ishan Fernando, Adeepa Fernando +3
Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide, accounting for over 30% of global deaths according to the World Health Organization (WHO). Importantly,…
Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics
Michael A. Riegler, Kristoffer Herland Hellton, Vajira Thambawita +1
Selecting prior distributions in Bayesian statistics is challenging, resource-intensive, and subjective. We analyze using large-language models (LLMs) to suggest suitable, knowledg…
AI-assisted radiographic analysis in detecting alveolar bone-loss severity and patterns
Chathura Wimalasiri, Piumal Rathnayake, Shamod Wijerathne +5
Periodontitis, a chronic inflammatory disease causing alveolar bone loss, significantly affects oral health and quality of life. Accurate assessment of bone loss severity and patte…
SoccerChat: Integrating Multimodal Data for Enhanced Soccer Game Understanding
Sushant Gautam, Cise Midoglu, Vajira Thambawita +3
The integration of artificial intelligence in sports analytics has transformed soccer video understanding, enabling real-time, automated insights into complex game dynamics. Tradit…
Merging synthetic and real embryo data for advanced AI predictions
Oriana Presacan, Alexandru Dorobantiu, Vajira Thambawita +5
Accurate embryo morphology assessment is essential in assisted reproductive technology for selecting the most viable embryo. Artificial intelligence has the potential to enhance th…
Comparative Analysis of Audio Feature Extraction for Real-Time Talking Portrait Synthesis
Pegah Salehi, Sajad Amouei Sheshkal, Vajira Thambawita +5
This paper examines the integration of real-time talking-head generation for interviewer training, focusing on overcoming challenges in Audio Feature Extraction (AFE), which often…
SoccerNet-Echoes: A Soccer Game Audio Commentary Dataset
Sushant Gautam, Mehdi Houshmand Sarkhoosh, Jan Held +7
The application of Automatic Speech Recognition (ASR) technology in soccer offers numerous opportunities for sports analytics. Specifically, extracting audio commentaries with ASR…
Biomedical image analysis competitions: The state of current participation practice
Matthias Eisenmann, Annika Reinke, Vivienn Weru +352
The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known abou…
Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge
Sharib Ali, Noha Ghatwary, Debesh Jha +29
Polyps are well-known cancer precursors identified by colonoscopy. However, variability in their size, location, and surface largely affect identification, localisation, and charac…
MMSys'22 Grand Challenge on AI-based Video Production for Soccer
Cise Midoglu, Steven A. Hicks, Vajira Thambawita +2
Soccer has a considerable market share of the global sports industry, and the interest in viewing videos from soccer games continues to grow. In this respect, it is important to pr…
Meta-learning with implicit gradients in a few-shot setting for medical image segmentation
Rabindra Khadga, Debesh Jha, Steven Hicks +4
Widely used traditional supervised deep learning methods require a large number of training samples but often fail to generalize on unseen datasets. Therefore, a more general appli…