Hospital-Based Medicine

SmartAlert: Integrating Machine Learning and Alert Triggers into Live Electronic Medical Record Systems, Targeting Low-Yield Inpatient Lab Tests

This study explores integrating machine learning into electronic medical record systems to predict stability of inpatient lab tests. A 'SmartAlert' system was developed and tested at Stanford Hospital. The system identifies stable lab results, advising clinicians on test ordering. Live deployment showed desired precision at good recall in predicting test result stability, with suggestions for syst...

From Data Lifting to Continuous Risk Estimation: A Process-Aware Pipeline for Predictive Monitoring of Clinical Pathways

This paper presents a reproducible and process-aware pipeline for predictive monitoring of clinical pathways. The approach integrates data lifting, temporal reconstruction, event log construction, prefix-based representations, and predictive modeling to support continuous reasoning on partially observed patient trajectories, overcoming the limitations of traditional retrospective process mining. T...

Development and Validation of Machine Learning Models for Predicting Mortality in Hospitalised Systemic Lupus Erythematosus Patients in Dr. Sardjito Hospital, Indonesia Machine Learning Prediction of In-Hospital Mortality in SLE

Objectives This study aimed to develop and validate machine learning models to predict in-hospital mortality among systemic lupus erythematosus (SLE) ...

Temporal Data Requirement for Predicting Unplanned Hospital Readmissions

With the proliferation of Electronic Health Records (EHRs), a critical challenge in building predictive models is determining the optimal historical d...

Development and Validation of a Two-Stage NLP-LLM System for Automated Extraction of Deprescribing Recommendations from Discharge Summaries

Introduction: Polypharmacy in older adults is associated with increased risks of adverse drug events and functional decline. Discharge summaries often...

SlicerRoboTMS: An Open-Source 3D Slicer Extension for Robot-Assisted Transcranial Magnetic Stimulation

Robot-assisted Transcranial Magnetic Stimulation (Robo-TMS) is an image-guided robotic intervention that enhances the accuracy and reproducibility of ...

Focus on What Matters: Two-Stage ROI-Aware Refinement for Anatomy-Preserving Fetal Ultrasound Reconstruction

Measurement-critical ultrasound tasks often depend on a small anatomical region, making global reconstruction metrics an unreliable proxy for clinical...

Comparing prognostic performance and reasoning between large language models and physicians

Importance: Physicians routinely prognosticate to guide care delivery and shared decision making, particularly when caring for patients with critical ...

Prognosis of stroke subtypes in whole population health systems data: a matched cohort study

Background Outcome after stroke varies according to stroke subtype by location, but healthcare systems data studies do not include subtyping informati...

A Nationwide Japanese Medical Claims Foundation Model: Balancing Model Scaling and Task-Specific Computational Efficiency

Clinical risk prediction using longitudinal medical data supports individualized care. Self-supervised foundation models have emerged as a promising a...

An Integrated Framework for Explainable, Fair, and Observable Hospital Readmission Prediction: Development and Validation on MIMIC-IV

Objective: To propose and retrospectively validate an integrated framework addressing three barriers to clinical translation of readmission prediction...

A Systematic Exploration of LLM Behavior for EHR phenotyping

Background Electronic health record (EHR) phenotyping underpins observational research, cohort discovery, and clinical trial screening. Large language...

Generalizing intensive care AI across time scales in resource-limited settings

Temporal resolution of physiological monitoring in intensive care varies widely across healthcare systems. Artificial intelligence models assume a uni...

A multimodal and temporal foundation model for virtual patient representations at healthcare system scale

Modern medicine generates vast multimodal data across siloed systems, yet no existing model integrates the full breadth and temporal depth of the clin...

AstroVLM: Expert Multi-agent Collaborative Reasoning for Astronomical Imaging Quality Diagnosis

Vision Language Models (VLMs) have been applied to several specific domains and have shown strong problem-solving capabilities. However, astronomical ...

Aakhyan: An AI-Powered Vernacular Patient Communication Platform for Oncology in Resource-Limited Settings - System Architecture and Pilot Randomised Trial Protocol

Inadequate discharge communication is a well-documented contributor to medication non-adherence, missed follow-ups, and preventable readmissions acros...

No One Left Behind: Adaptive Tablet Modalities for Digitally Excluded Emergency Department Patients Design, Implementation, and Social Evidence for an Impairment-First Interface

Background: The urgent care departments in Europe face a structural paradox: accelerating digitalisation is accompanied by a patient population that i...

Wearable sleep staging using photoplethysmography and accelerometry across sleep apnea severity: a focus on very severe sleep apnea

Study ObjectivesTo evaluate wearable sleep staging across sleep apnea severity, including very severe sleep apnea defined as an apnea-hypopnea index (...

Vision Transformers for Preoperative CT-Based Prediction of Histopathologic Chemotherapy Response Score in High-Grade Serous Ovarian Carcinoma

Purpose. High-grade serous ovarian carcinoma (HGSOC) is characterized by pronounced biological and spatial heterogeneity and is frequently diagnosed a...

A Utility-preserving De-identification Pipeline for Cross-hospital Radiology Data Sharing

Large-scale radiology data are critical for developing robust medical AI systems. However, sharing such data across hospitals remains heavily constrai...