Given the widespread prevalence of depression and its consequential impact on individuals and society, it is crucial to obtain objective measures for early diagnosis and intervention. As a multidisciplinary topic, these objective measures should be interpretable and accessible to health care professionals, ensuring effective collaboration and treatment planning in the realm of mental health care.
The paper evaluates deep learning models for electrocardiogram‑based emotion recognition, focusing on generalization across datasets rather than dataset‑specific performance. It introduces two open‑source tools—ARRC for standardized benchmarking and ARDT for inter‑dataset training—to merge three public AER datasets (CUADS, ASCERTAIN, DREAMER) into a more variable benchmark. Using these tools, the authors compare three prominent deep learning architectures and two CNN baselines with hyperparameter tuning and 10‑fold cross‑validation, revealing trade‑offs between accuracy and model complexity and providing a reproducible benchmark for future research.
By Timothy C Sweeney-Fanelli, Ajan Ahmed, Masudul Imtiaz
arXiv:2606. 17437v1 Announce Type: cross Abstract: Automated classification of standard echocardiographic views is crucial for efficient clinical workflow but faces three main challenges.
By Bo Gou, Jicheng Zhang, Jianlong Xiong, Tao He, Bentian Liu, Hai Wu, Yijiao Wang, Yu Zhang, Yujia Yang, Yun Dai, Jian Liu, Jie Wang
arXiv:2604. 11730v4 Announce Type: replace-cross Abstract: Using behavioural science, health interventions focus on behaviour change by providing a framework to help patients acquire and maintain healthy habits that improve medical outcomes.
By Manuela Gonz\'alez-Gonz\'alez, Soufiane Belharbi, Muhammad Osama Zeeshan, Masoumeh Sharafi, Muhammad Haseeb Aslam, Lorenzo Sia, Nicolas Richet, Marco Pedersoli, Alessandro Lameiras Koerich, Simon L Bacon, Eric Granger
arXiv:2609.22631v1 Announce Type: new
Abstract: Accurate automated interpretation of electrocardio- grams (ECGs) is essential for early detection of cardiac condi- tions such as myocardial infarction...
By Mohammad Sadman Tahsin, Haitham Y. Adarbah, Afzel Noore
arXiv:2512. 21414v2 Announce Type: replace-cross Abstract: Recent tool-use frameworks powered by vision-language models (VLMs) improve image understanding by grounding model predictions with specialized tools.
By Christina Liu, Alan Q. Wang, Joy Hsu, Jiajun Wu, Ehsan Adeli