arXiv Machine Learning

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning

arXiv:2606. 02998v1 Announce Type: new Abstract: Automated cough analysis offers a path to low-cost respiratory screening, but most existing work stops at binary COVID-19 detection.

arXiv Machine Learning

Jul 27

Autoregressive EHR Foundation Models with Multimodal Inputs

arXiv:2607. 22264v1 Announce Type: new Abstract: Autoregressive foundation models trained on tokenized electronic health records (EHRs) can support zero-shot clinical prediction, yet most operate on structured event codes alone, and do not incorporate multiple modalities in a principled way.

By Yuxuan Liu, Joshua Placidi, Jinpei Han, Alfred John Balston, Marek Rei, A. Aldo Faisal

multimodal safety

arXiv AI

Jun 9

AeroSpectra Sentinel: An Auditable LLM Prompt-Chaining Decision-Support Workflow for Acute Asthma Risk Assessment from Respiratory Sounds and Clinical Signals

arXiv:2606. 08247v1 Announce Type: cross Abstract: Acute asthma risk assessment requires rapid interpretation of respiratory sounds, oxygenation, airflow limitation, speech ability, work of breathing, mental status, and response to reliever therapy.

By Aueaphum Aueawatthanaphisut

llms safety data-engineering

arXiv AI

Jul 16

MedDiffuseMix: Preserving Diagnostic Evidence with Saliency-Aware Diffusion Medical Image Data Augmentation

arXiv:2606. 28419v2 Announce Type: replace-cross Abstract: Limited data availability, class imbalance, and domain variability remain major barriers to reliable medical image classification.

By Teerath Kumar, Raja Vavekanand, Muhammad Turab

llms diffusion computer-vision benchmarks

arXiv AI

Jun 30

MedDiffuseMix: Preserving Diagnostic Evidence with Saliency-Aware Diffusion Medical Image Data Augmentatio

arXiv:2606. 28419v1 Announce Type: cross Abstract: Limited data availability, class imbalance, and domain variability remain major barriers to reliable medical image classification.

By Teerath Kumar, Raja Vavekanand, Muhammad Turab

llms diffusion computer-vision benchmarks

arXiv AI

Jun 16

Beyond Classification: A Cough Regression Benchmark for Respiratory Acoustic Foundation Models

arXiv:2606. 15436v1 Announce Type: cross Abstract: Respiratory acoustic foundation models (FMs) excel at cough classification, yet their ability to predict continuous health quantities from cough audio remains largely unexplored, despite the clinical value of passive age, BMI, and disease probability estimation in settings where physical measurements are unavailable.

By Mayur Sanap, Prasanna Desikan, Edgar Lobaton

benchmarks

arXiv Machine Learning

Jun 9

Label-Conditioned Cross-Modal Fusion for Adult-to-Pediatric ECG Transfer via Curriculum-Gated Contrastive Alignment

arXiv:2605. 00647v2 Announce Type: replace Abstract: Automated pediatric electrocardiogram (ECG) interpretation remains challenging because developmental differences in heart rate, intervals, and waveforms limit the transferability of models trained mainly on adult data, while expert-labeled pediatric ECG cohorts are scarce.

By Xinran Liu, Yuwen Li, Hongxiang Gao, Heyang Xu, Jianqing Li, Zongmin Wang, Chengyu Liu

fine-tuning multimodal safety

arXiv AI

Jun 16

Fusion is not one-size-fits-all: Cross-Modal Representation Alignment for Time-to-Event Modeling

arXiv:2606. 15038v1 Announce Type: new Abstract: Accurate time-to-event (TTE) prediction from multimodal clinical data remains challenging due to modality imbalance and distribution shift.

By Zhemin Zhang, Weijie Chen, David Le, Amara Tariq, Alex Wallace, Matthew Stib, Juan Maria Farina, Chadi Ayoub, Reza Arsanjani, Imon Banerjee

diffusion multimodal safety

arXiv AI

Jun 10

Optimizing 2D Input Representations and Sub-phase Fusion Strategies for Differential Diagnosis of Asthma and COPD Using CNN- and GRU-Based Networks

arXiv:2606. 10972v1 Announce Type: cross Abstract: This study aims to explore the performance of the VAR model in comparison with mel-frequency cepstral coefficient (MFCC) matrices and log-mel spectrograms using deep learning.

By Ipek Sen, Ozgur Ozdemir, Elena Battini Sonmez

arXiv AI

Jul 7

PulmoSight-XAI: An Explainable Multi-View Attention Ensemble with Gradient Boosting Meta-Learning for Multi-Label Chest X-Ray Classification

arXiv:2607. 04478v1 Announce Type: cross Abstract: Automated chest X-ray classification remains challenging due to severe class imbalance, co-occurring pathologies, and the loss of localized features in conventional architectures.

By Moshiur Rahman, Shafqat Alam, Tasnia Binte Mamun

benchmarks

arXiv AI

Jul 21

Hierarchy-Aware and Anatomy-Guided Learning for Lung Ultrasound Video Classification

arXiv:2607. 17551v1 Announce Type: cross Abstract: Lung ultrasound (LUS) is a bedside tool for assessing pulmonary edema in patients at risk due to heart failure or impaired kidney function.

By Alya Almsouti, Lotfi Mecharbat, Noha Aboukhater, Yousef Alabrach, Siddiq Anwar, Andre Kumar, Ibrahim Almakky, Mohammad Yaqub

arXiv Machine Learning

6d ago

Look What the Probes Dragged In! Real-World Chest X-ray Shortcuts in MedCLIP

arXiv:2608. 12086v1 Announce Type: cross Abstract: Vision-language models, such as contrastive language-image pre-training (CLIP)-based approaches, have reached state-of-the-art (SOTA) results in medical artificial intelligence.

By Nikolette Pedersen, Regitze Sydendal, Veronika Cheplygina, Th\'eo Sourget

llms multimodal benchmarks data-engineering

arXiv AI

Jun 2

A Novel Data Augmentation Strategy for Robust Deep Learning Classification of Biomedical Time-Series Data: Application to ECG and EEG Analysis

arXiv:2507. 12645v1 Announce Type: cross Abstract: The increasing need for accurate and unified analysis of diverse biological signals, such as ECG and EEG, is paramount for comprehensive patient assessment, especially in synchronous monitoring.

By Mohammed Guhdar, Ramadhan J. Mstafa, Abdulhakeem O. Mohammed

benchmarks

Related stories