Hospital-Based Medicine

Surveillance

Latest AI and machine learning research in surveillance for healthcare professionals.

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AI Implementation in U.S. Healthcare and Its Association With Elder Mortality and Quality of Care

Hospitals are increasingly adopting artificial intelligence (AI) tools in clinical care. However, th...

Evaluation of Large Language Models in Medical Examinations: A Scoping Review Protocol

Large language models (LLMs) demonstrate human-level performance in three key domains: linguistic un...

Natural Language Processing Techniques to Detect Delirium in Hospitalized Patients from Clinical Notes: A Systematic Review

Delirium is a serious and common condition in hospitalized patients, associated with increased morbi...

Granular Insights:A Wastewater-Based Machine Learning Approach for Localized COVID-19 Hospitalization Forecasting

Wastewater based epidemiology (WBE) is a valuable tool for monitoring emerging disease trends in a c...

Development of Machine Learning Algorithms Using EEG Data to Detect the Presence of Chronic Pain

Chronic pain impacts more than one in five adults in the United States (US) and the costs associated...

Enhancing Fairness in Diabetes Prediction Systems through Smart User Interface Design

Artificial intelligence (AI) in chronic disease prediction often exhibits algorithmic biases, hinder...

Enhancing Cause of Death Prediction: Development and Validation of ML Models Using Multimodal Data Across Multiple Healthcare Sites

Timely and accurate determination of causes of death (CoD) is essential for public health surveillan...

Automatic ICD coding using LLMs: a systematic review

Manual assignment of International Classification of Diseases (ICD) codes is error-prone. Transforme...

Temperature-Driven Variability in Emergency Diagnostic Accuracy by a Leading Language Model

To determine the impact of the temperature parameter on GPT-4o’s diagnostic accuracy when evaluating...

Artificial Intelligence for Surgical Scene Understanding: A Systematic Review and Reporting Quality Meta-Analysis

Surgical scene understanding (SSU) describes the use of Artificial Intelligence (AI) to provide an u...

Calibrating CONSORT-AI with FAIR Principles to enhance reproducibility in AI-driven clinical trials

Artificial intelligence (AI) is increasingly embedded in clinical trials, yet poor reproducibility r...

Portability of an artificial intelligence model for self-harm detection across hospital settings

Adequate self-harm surveillance is a key part of suicide prevention efforts. Our prior work has demo...

Machine learning for medication error detection: a scoping review protocol

Medication errors pose a significant threat to public health. Despite efforts by health agencies and...

Complex pathways to ceftolozane-tazobactam resistance in clinical Pseudomonas aeruginosa isolates: a genomic epidemiology study

We aimed to conduct a comprehensive genomic analysis of ceftolozane/tazobactam (C/T) resistance mech...

External Validation of a Machine Learning Model to Predict Postpartum Hemorrhage in a US Northeastern Healthcare System

Postpartum hemorrhage (PPH) is a major cause of maternal morbidity and mortality. Timely prediction ...

Incidence, Outcomes and Risk Factors of Cardiac Arrest Among Surgical Patients in the UK Biobank: A Population-Based Cohort Study

Perioperative cardiac arrest (CA) is a devastating surgical complication, yet its epidemiology and r...

Association between zidovudine and adverse pregnancy outcomes/congenital malformations: A pharmacovigilance study using FAERS data

Zidovudine (AZT), a key antiretroviral drug used for HIV treatment and preventing mother-to-child tr...

Explainable AI to predict a complex multifactorial outcome, childhood obesity: Application to clinical epidemiology

Childhood obesity, driven by genetic and epidemiological factors, poses significant health risks, ye...

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