Hospital-Based Medicine

Antimicrobial resistance analysis of Klebsiella pneumoniae bloodstream infections based on a random forest algorithm: a longitudinal study based on data from tertiary hospitals in China from 2012 to 2023.

BACKGROUND: Bloodstream infections (BSIs) caused by Klebsiella pneumoniae pose a significant global health burden, complicated by rising antimicrobial resistance (AMR). This study aimed to characterize resistance patterns, identify predictors of carbapenem resistance, and develop a machine learning model to predict patient outcomes. METHODS: In a retrospective analysis of 109 279 K. pneumoniae BSI...

Development and Clinical Utility of Machine Learning Models for Prediction of Same-Day Discharge in Outpatient Hip and Knee Replacement: A Prognostic Study.

BACKGROUND: Hip and knee replacement are common procedures with an increasing focus on same-day surgery. However, capacity constraints limit the number of eligible patients actually being scheduled for same-day discharge, calling for further selection of those with the highest likelihood of same-day discharge. METHODS: A prognostic study from September 2022 to April 2024 aiming to develop and eval...

Harnessing Artificial Intelligence to Strengthen Acute and Critical Care Nursing Practice: A Systematic Review.

BACKGROUND: Artificial intelligence (AI) is reshaping clinical decision support systems (CDSSs). In acute and critical care, nurses provide continuous...

Natural language processing to develop a standardized lexicon for precision medicine in oncology.

Precision medicine terminology is increasingly used across clinical, laboratory, payer, regulatory, and policy settings; however, distinct terminology...

An informatics framework to harmonize electronic health record medication data for managed care analytics and artificial intelligence applications.

BACKGROUND: Artificial intelligence (AI) applications in managed care pharmacy depend on semantically consistent medication data, yet heterogeneous me...

Artificial intelligence-enabled causal estimate of Medicare drug plan integration in cancer care: A doubly robust machine learning instrumental variable analysis.

BACKGROUND: Artificial intelligence (AI) methods are increasingly used to strengthen policy evaluation in managed care pharmacy. Among Medicare benefi...

Leveraging Artificial Intelligence to Improve Perioperative Staffing Consistency: A Quality Improvement Initiative at a Large Academic Medical Center.

A large academic medical center in the Pacific Northwest addressed perioperative staffing challenges by implementing a workflow with application of AI...

Evaluating the Accuracy, Empathy, and Readability of Generative AI Versus Registered Nurses in Discharge Planning: A Vignette-Based Study.

AIM: To compare the multidimensional performance of discharge instructions generated by generative AI (GPT-4) versus those created by clinical registe...

The Digital Transformation of Rehabilitation Medicine: A Narrative Review of Artificial Intelligence Innovations, Clinical Integration, and Future Paradigms.

BACKGROUND: Traditional rehabilitation medicine, primarily dependent on qualitative clinical assessment and static therapeutic protocols, faces signif...

Elevated pro-BNP and low-grade inflammation are associated with low bone mineral density in systemic sclerosis, a case control study.

BACKGROUND: Bone mineral density (BMD) is compromised in patients with systemic sclerosis (SSc) compared to the background population, yet the underly...

Effect of a Machine Learning Algorithm to Guide Goal-Directed Therapy After Cardiac Surgery.

BACKGROUND: Goal-directed therapy allows clinicians to optimize perfusion and volume status in patients postoperatively. OBJECTIVE: To evaluate the ef...

Cancer-associated fusion transcripts: mechanisms, functional roles, and clinical implications.

Fusion transcripts are hybrid RNA molecules generated through genomic rearrangements or RNA-level fusion mechanisms. They represent important molecula...

Investigating Whether Summarizing Raw Clinical Text Affects the Prediction of In-Hospital Violence: A Retrospective Case Study: Évaluation de l'effet du résumé des textes cliniques bruts sur la prédiction de la violence en milieu hospitalier : étude de cas rétrospective.

BackgroundWe evaluated whether summaries and large language models (LLMs) preserve predictive performance for inpatient violence risk and assessed per...

Machine Learning-Driven Risk Clusters for Adverse Outcomes in Patients Hospitalized with Acute Heart Failure: Using a Retrospective Cohort Data.

AIM: Heart failure (HF) poses a growing public health burden, yet conventional risk stratification models fail to capture the multidimensional complex...

Comparison of artificial intelligence and multidisciplinary team assessment for evaluating biologic decisions in severe uncontrolled asthma.

BACKGROUND: The management of severe asthma with biologics has become more complex involving multidisciplinary team meetings. Artificial intelligence ...

Integrating Artificial Intelligence into Venous Thromboembolism Care: Predictive Models, Implementation Challenges, and Future Directions.

Artificial intelligence (AI) has the potential to support personalized, multidisciplinary, data-driven care for venous thromboembolism (VTE) preventio...

Identification of comorbidity-based clusters and mortality risk in hospitalised patients with diabetes mellitus in Karachi, Pakistan: a machine learning analysis.

BACKGROUND: Diabetes has reached epidemic proportions in Pakistan. This study applied machine learning (ML) techniques to identify comorbidity-based a...

Prospective economic evaluation of a predictive artificial intelligence model for sepsis: Effects on hospital costs and return on investment.

Early sepsis detection is essential for improving outcomes and reducing costs, but traditional rule-based systems have limited accuracy and real-world...

Operational AI Adoption in U.S. Inpatient Rehabilitation Facilities: Organizational Selection and Domain Heterogeneity, 2021-2024.

OBJECTIVE: To examine Inpatient Rehabilitation Facilities, market, and regional characteristics associated with operational AI adoption across three f...

Evaluation of Large Language Model-Generated Recommendations in Glaucoma Surgical Decision-Making.

OBJECTIVE: To evaluate the utility, rationality, and safety of glaucoma surgery recommendations generated by three prominent large language models (LL...