Hospital-Based Medicine

Use of AI to Predict and Support Medication Adherence in Patients With Breast Cancer: Systematic Review.

BACKGROUND: Oral medications are commonly used in the treatment of breast cancer (BC), despite high rates of nonadherence. As adherence is fundamental for optimal treatment, finding ways to effectively improve it is important. Artificial intelligence (AI) is being widely applied to health care. OBJECTIVE: This review aims to offer an overview of the contribution of AI to medication nonadherence am...

Engaging Hospital Staff to Identify Levers for Adoption of Clinical Decision Support: Protocol for a Single-Site Case Study Using System Dynamics Group Model Building.

BACKGROUND: Clinical decision support (CDS) tools that provide patient-specific and evidence-based information to clinicians and care managers regarding patient risk for adverse outcomes have been a part of health care for decades. However, modern CDS, which consists of automated predictions based on complex machine learning models and hundreds of complex input variables, faces obstacles to adopti...

Classifying American Society of Anesthesiologists Physical Status With a Low-Rank-Adapted Large Language Model: Development and Validation Study.

BACKGROUND: The American Society of Anesthesiologists Physical Status (ASA-PS) classification is integral to preoperative risk assessment; yet, assign...

IPEM Topical Report: A National Survey of MRI Use for External Beam Radiotherapy Treatment Planning in the UK: 2025 IPEM Survey Results.

Magnetic Resonance Imaging (MRI) offers superior soft tissue contrast compared to Computed Tomography (CT), making it highly valuable in external beam...

The Hospital Organ Donation Performance Score: A human and artificial intelligence/machine learning collaborative solution to the current nationwide puzzling state of organ donation metrics.

BACKGROUND: Efforts to ameliorate the current organ shortage have predominantly focused on improving processes among the nation's organ procurement or...

From prediction to practice: early implementation of a machine learning-based hospitalization prediction tool in the emergency department.

BACKGROUND: Machine learning (ML) models can accurately predict hospital admissions in emergency departments (EDs), but real-world adoption remains ra...

In vivo CAR-cell therapy: current challenges and emerging therapeutic advances.

In vivo chimeric antigen receptor (CAR) cell therapy is undergoing a transformative shift from conventional ex vivo manufacturing toward in situ cellu...

Detection of calcified plaques: comparison between coronary CT angiography and thin-slice non-contrast CT with deep learning-aided image registration.

OBJECTIVES: To investigate whether coronary CT angiography (CCTA) misses calcified plaques detected by thin-slice non-contrast CT (NCCT). MATERIALS AN...

The future of follow-up: technology-enabled medical and developmental follow-up care for NICU graduates.

Premature infants are at higher risk of long-term clinical and developmental sequelae compared to their term counterparts. Specialized, multidisciplin...

Interpretable machine learning for river salinity dynamics in arid basins.

Managing salinity in arid rivers is impeded by sparse monitoring, relying on low-frequency grab samples that miss hydrological event dynamics. Here, i...

Turbocharging crop breeding with integrated biotechnology for a climate-resilient future.

Global agriculture faces unprecedented challenges from climate change and population growth, creating an urgent demand for the rapid development of re...

Power transformer online monitoring and state assessment method based on 2DCNN-BiLSTM multi-source feature fusion.

As key power system equipment, real-time monitoring and accurate assessment of power transformers' operating status are critical for grid safety. To a...

Non-European migrants with schizophrenia spectrum disorders in Swiss forensic and general psychiatric care facilities - A comparative study using machine learning.

Personal history of migration poses an important risk factor for schizophrenia spectrum disorders (SSD), which are also associated with a higher rate ...

Use of Large Language Models to Enhance Failure Mode and Effects Analysis: A Case Study.

PURPOSE: Failure Mode and Effects Analysis (FMEA) is widely used in radiation oncology to proactively identify and mitigate risks, but it is time-cons...

[Current status and future perspectives of precision treatment for locally advanced rectal cancer].

The treatment paradigm for locally advanced rectal cancer is undergoing a fundamental transformation from the traditional fixed triad of "radiotherapy...

[Exploration and clinical application of the "digital and intelligent surgery" diagnosis and treatment workflow for oral and maxillofacial tumors].

Tumors in the oral and maxillofacial region present significant clinical challenges due to anatomical complexity and high individual variability, with...

Outcomes of perioperative intra-aortic balloon pump support in patients undergoing aortic valve surgery: A single-centre, retrospective, observational study.

BACKGROUND: Patients undergoing aortic-valve surgery are prone to perioperative low-cardiac-output syndrome or progression to cardiogenic shock, which...

Multiparametric AI-based perfusion analysis outperforms Tmax thresholding for critically hypoperfused tissue estimation in acute ischemic stroke undergoing admission MRI.

OBJECTIVE: Perfusion imaging is used to estimate critically hypoperfused tissue in acute ischemic stroke (AIS), commonly using threshold-based methods...

Ensemble Machine Learning Models for Predicting Death in Post-Acute Skilled Nursing Facilities.

OBJECTIVE: Patients discharged from hospitals to skilled nursing facilities (SNFs) for post-acute care are at high risk for adverse outcomes, includin...

Development of a real-world, therapeutic drug monitoring-informed model to predict teicoplanin daily dose in pediatric intensive care unit patients with bacterial infections.

INTRODUCTION: Teicoplanin is commonly used to treat Gram-positive bacterial infections in the intensive care unit (ICU). However, evidence to support ...