Hospital-Based Medicine

Telepathology and Mobile Health System for Province-Wide Pathology Consultation in Henan, China: Retrospective Evaluation Study.

BACKGROUND: Telepathology has emerged as a transformative digital health solution to address the global shortage of pathologists and the unequal distribution of diagnostic services, particularly in underserved and rural areas. In Henan Province, China, high diagnostic demand, rapid population growth, and limited pathology expertise exacerbate regional health care inequities, leading to delayed dia...

Improving Maternal Health Equity and Outcomes Through the Development of a Clinician-Informed Algorithm: A Feasibility Study.

OBJECTIVE: Increasing proportions of adverse maternal health outcomes occur in the 12-month postpartum period and could be addressed in outpatient settings. Our objective was to develop and test an algorithm to support a population health tool to identify high-risk prenatal patients served by federally qualified health centers (FQHCs). METHODS: We leveraged human-centered design to develop and tes...

Machine Learning in Discharge Planning for Stroke Patients: A Review of Feature Representation and Aggregation Strategies With Suggestions for Improvement.

The utility of large language models in oncological multidisciplinary team meetings: A systematic review.

Large language models (LLMs) have emerged in recent years as innovative artificial intelligence systems with early potential in clinical decision-maki...

[Evaluation of Chinese artificial intelligence large language models in oral mucosal disease consultation].

Objective: To investigate the current application status and potential of artificial intelligence (AI) large language models (LLMs) in oral mucosal di...

[Deep learning-based assessment of periodontal ligament area changes in maxillary central incisors under different orthodontic regimens using cone-beam CT images].

Objective: To investigate the differences in the changes of periodontal ligament area (PDLA) and related clinical indicators before and after maxillar...

MS360°: a conceptual digital-first, data-driven hybrid care framework for personalised multiple sclerosis management.

This perspective introduces MS360°, a conceptual hybrid care model for the management of multiple sclerosis (MS). It integrates traditional on-site as...

Association between stress hyperglycemia ratio and all-cause mortality in neurocritical patients.

Fluctuations in blood glucose during acute neurocritical illness are associated with poor outcomes, but the role of stress hyperglycemia ratio (SHR) i...

Multidisciplinary Optimization Design of pVADs Using Analytical Target Cascading-Guided Genetic Algorithm.

PURPOSE: The purpose of this article is to address the limitations of inconsistency between the impeller and motor when designing Percutaneous ventric...

Predictive divergence in machine learning models for clinical mortality risk: A multicohort study of covid-19 patients.

BACKGROUND: Machine learning (ML) algorithms are increasingly used in healthcare to support clinical decision-making. While models with similar overal...

Phenotypic clustering of myocardial infarction complicated by out-of-hospital cardiac arrest using unsupervised machine learning.

BACKGROUND: Patients with myocardial infarction (MI) complicated by out-of-hospital cardiac arrest (OHCA) represent a heterogeneous population with va...

Identifying patients at risk for short-term adverse events after hip arthroscopy: a machine learning analysis of a national database.

PURPOSE: To develop and compare machine learning-based risk prediction models to identify patients at risk for short-term adverse outcomes (overnight ...

Association of surgical resection with survival in retroperitoneal leiomyosarcoma based on SEER propensity score matching and machine-learning models.

Retroperitoneal leiomyosarcoma (RLS) is a rare and aggressive subtype of soft tissue sarcoma with limited population-level evidence guiding surgical d...

Highlights from the Italian National Congress of Imaging in Pulmonology 2025: fostering implementation of advanced technologies for precision patient-centered care.

The Italian National Congress of Imaging in Pulmonology, held in Milan on November 21st, provided a unique educational platform exploring the evolving...

An AI-assisted framework for the ethical use of machine learning in healthcare.

This study develops and evaluates ETHICS, a concise, clinician-facing ethical protocol for the routine use of machine learning (ML) in healthcare. Usi...

CTKGR: temporal knowledge graph enhanced prediction of in-hospital events for pneumonia patients using electronic health records.

OBJECTIVE: This study aims to develop an advanced clinical event prediction model leveraging the temporal characteristics embedded within electronic h...

Natural Language Processing and Machine Learning Classification Model for Injury Mechanism in Trauma.

INTRODUCTION: Creating and maintaining research databases in trauma can be resource intensive. Natural language processing (NLP) may assist by extract...

Machine Learning-Enhanced TCAB Score for Predicting Postoperative Ischemic Stroke After CABG.

BACKGROUND: Postoperative acute ischemic stroke remains a critical complication of coronary artery bypass grafting. This study aimed to develop a nove...

Association between deep learning-based atrial fibrillation burden and in-hospital mortality.

Despite its clinical significance, research on atrial fibrillation (AF) burden as a dynamic, real-time predictor of adverse outcomes in patients with ...

Toward accurate prediction of pediatric epidemic disease patient volume in the Chaoshan region: A deep learning framework.

Accurate prediction of pediatric epidemic infectious diseases is critical for effective prevention and personalized treatment. Herein, we developed a ...