7 citations · 7 across the 11 of their papers we have counts for
11 papers
Quality Adaptive Angular Margin Learning for Respiratory Sound Classification
Yoon Tae Kim, Heejoon Koo, Miika Toikkanen +1
We present a quality-adaptive angular-margin learning framework that improves feature generalization by enforcing intra-class compactness and inter-class separability. Our framewor…
Mitigating Stethoscope-Induced Shortcuts in Respiratory Sound Classification under Federated Domain Generalization with Causality-Inspired Interventions
Heejoon Koo, Yoon Tae Kim, Miika Toikkanen +1
AI-driven respiratory sound classification (RSC) is promising for automated pulmonary disease detection, yet multi-site deployment is hindered by inter-stethoscope variability. We…
Can Large Audio Language Models Ignore Multilingual Distractors? An Evaluation of Their Selective Auditory Attention Capabilities
Heejoon Koo
Robust selective auditory attention under multilingual interference is critical for reliable LALM deployment. We introduce MUSI, a cocktail party-inspired controlled diagnostic eva…
Meta-Ensemble Learning with Diverse Data Splits for Improved Respiratory Sound Classification
June-Woo Kim, Miika Toikkanen, Heejoon Koo +3
Training reliable respiratory sound classification models remains challenging due to the limited size and subject diversity of datasets. Ensemble methods can improve robustness, bu…
Dual-Margin Embedding for Fine-Grained Long-Tailed Plant Taxonomy
Cheng Yaw Low, Heejoon Koo, Jaewoo Park +1
Taxonomic classification of ecological families, genera, and species underpins biodiversity monitoring and conservation. Existing computer vision methods typically address fine-gra…
Towards Robust and Fair Next Visit Diagnosis Prediction under Noisy Clinical Notes with Large Language Models
Heejoon Koo
A decade of rapid advances in artificial intelligence (AI) has opened new opportunities for clinical decision support systems (CDSS), with large language models (LLMs) demonstratin…
Empowering Multimodal Respiratory Sound Classification with Counterfactual Adversarial Debiasing for Out-of-Distribution Robustness
Heejoon Koo, Miika Toikkanen, Yoon Tae Kim +2
Multimodal respiratory sound classification offers promise for early pulmonary disease detection by integrating bioacoustic signals with patient metadata. Nevertheless, current app…
Overcoming Uncertain Incompleteness for Robust Multimodal Sequential Diagnosis Prediction via Curriculum Data Erasing Guided Knowledge Distillation
Heejoon Koo
In this paper, we present NECHO v2, a novel framework designed to enhance the predictive accuracy of multimodal sequential patient diagnoses under uncertain missing visit sequences…
Next Visit Diagnosis Prediction via Medical Code-Centric Multimodal Contrastive EHR Modelling with Hierarchical Regularisation
Heejoon Koo
Predicting next visit diagnosis using Electronic Health Records (EHR) is an essential task in healthcare, critical for devising proactive future plans for both healthcare providers…
Diagonal Hierarchical Consistency Learning for Semi-supervised Medical Image Segmentation
Heejoon Koo
Medical image segmentation, which is essential for many clinical applications, has achieved almost human-level performance via data-driven deep learning technologies. Nevertheless,…
A Comprehensive Survey on Generative Diffusion Models for Structured Data
Heejoon Koo, To Eun Kim
In recent years, generative diffusion models have achieved a rapid paradigm shift in deep generative models by showing groundbreaking performance across various applications. Meanw…