arXiv:2607. 25340v1 Announce Type: new Abstract: The same episode of atrial fibrillation is a minor finding in a healthy adult and grounds for anticoagulation in an elderly patient with hypertension: identical signal, opposite decision.
By Sukju Oh, Moo-Yong Rhee, Jae-Sik Jang, Sukkyu Sun
The study introduces TRACER, a Transformer-based model that uses contrastive event representation to predict timelines leading to heart failure hospitalizations from low-resolution, irregularly sampled telemonitoring data. TRACER incorporates time-aware embeddings, contrastive pre‑training for anomaly detection, and independent binary classifiers, and was evaluated on biomarker sequences from 276 heart failure patients. The model achieved 66.7% accuracy in predicting hospitalization timelines with a 7.9% overestimation, outperforming other tested models by reformulating training as an event detection problem.
By Erik Aerts, Yinan Yu, Annika Rosengren, Michael Fu, Martin Lindgren, Falk Dippel, Martin Adiels, Helen Sj\"oland
The paper investigates how to evaluate bounded model updates for ICU prediction models using the MIMIC‑IV database. After auditing the data for recording artifacts and cleaning it, the authors compare a bounded update that retrains only treatment‑context and fusion parameters with full fine‑tuning across two model families and two targets, finding that bounded updates are non‑inferior or superior in most cases but depend on target, model family, and learning‑rate tuning. The study also shows that audits should precede update evaluation and that the update boundary should be chosen per target.
By Fatema Ferdous Tamanna, K. M. Merajul Arefin, Md. Abdul Masud
arXiv:2607. 19020v2 Announce Type: replace-cross Abstract: Clinical decision support degrades as treatment protocols evolve, but the obstacle to updating a deployed model is governance as much as accuracy: once retraining touches every parameter, no one can say afterwards where the update acted.
By Fatema Ferdous Tamanna, K. M. Merajul Arefin, Md. Abdul Masud
arXiv:2603. 25670v3 Announce Type: replace Abstract: Safety monitoring is essential for Cyber-Physical Systems (CPSs).
By John Ayotunde, Qinghua Xu, Guancheng Wang, Lionel C. Briand
arXiv:2608. 07759v1 Announce Type: cross Abstract: Cardiovascular AI models can classify clean elec- trocardiogram (ECG) signals, but real wearable signals change because of motion, breathing, posture, sensor contact, and true clinical deterioration.
By Farouk Ganiyu Adewumi, Timothy Oladunni, Rochak Ghimire, Kosisochukwu Ogbuanya, Sanaa Reeves, Sandy Akoy