Latest AI and machine learning research in hospital-based medicine for healthcare professionals.
Background Histological diagnosis of early-stage mycosis fungoides (MF) is hindered by profound overlap with benign inflammatory dermatoses (BIDs), leading to diagnostic delays and extensive ancillary testing. We developed MIMIC (Multiple Instance-learning for Identification of Mycosis fungoides In Cutaneous biopsies), a weakly supervised deep learning model designed as a triage tool at initial H&...
Disagreement-triggered escalation can create a structural blind spot in multi-agent arbitration: as base learners improve, they tend to converge, weakening safety monitoring where correlated failures concentrate. We term this correlated agreement blindness and present ARAT (Arbitrated Reasoning Agents for Alarm Triage), a directed-star system combining an inductive Random Forest (RF) agent, an ana...
Importance: Heart failure readmissions remain common following hospitalization, but accurately identifying which patients will be readmitted after dis...
Offline reinforcement learning (RL) has emerged as a promising framework for clinical decision support in sepsis, yet most existing studies focus excl...
Background: In Japan, acute inpatient care is divided into approximately 335 secondary medical care areas, which serve as the basic units for planning...
Background. UK clinical guidance recommends that structured risk prediction tools and risk stratification should not be used in self-harm, to predict ...
Federated learning (FL) enables multi-institutional training on clinical text without sharing raw data, but gradient inversion can reconstruct sensiti...
Background: Antimicrobial resistance poses a major threat to global public health. Large language models (LLMs) offer new possibilities for optimizing...
Abdominal aortic aneurysm (AAA) patients in the ICU represent a heterogeneous, high-risk population with mortality risk evolving across distinct clini...
Background: Documentation burden significantly impacts nursing workload and well-being, with nurses spending an estimated 20-40% of their time on docu...
Agentic research systems are emerging as a new paradigm for coordinating scientific workflows beyond isolated model inference, code generation, or sta...
Deep learning for EEG-based seizure detection faces critical challenges: severe annotation scarcity and extreme class imbalance, where ictal events co...
Large language models (LLMs) are increasingly deployed in online medical consultation, yet existing benchmarks remain poorly aligned with real clinica...
The Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) is a crucial but labor-intensive tool for managing SLE. We developed a privac...
Introduction: Standardizing fluid and vasopressor resuscitation in sep- tic shock is challenging due to patient heterogeneity. We trained a causal mod...
Inherently interpretable classifiers for tabular data typically rely on sparse features, rules, or patterns that users can inspect directly. The margi...
Unplanned readmissions after liver transplantation occur in over 30% of recipients, yet no validated prediction models exist, and prior observational ...
Background Hypercapnia may indicate a primary ventilatory syndrome, a complication of another illness, or an epiphenomenon of severe disease. The pres...
Background: Early risk stratification in traumatic brain injury (TBI) is essential for timely triage, resource allocation, and clinical decision-makin...
Background: Frailty is common in acute ischemic stroke (AIS) and predicts poor outcomes, but is not routinely captured in acute stroke care. Manual fr...