Hospital-Based Medicine

Latest AI and machine learning research in hospital-based medicine for healthcare professionals.

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Development and validation of inpatient mortality prediction models for patients with hyperglycemic crisis using machine learning approaches.

BACKGROUND: Hyperglycemic crisis is one of the most common and severe complications of diabetes mell...

[Therapeutic patient education and telemedicine in the age of artificial intelligence].

Since the promulgation of the July 21, 2009 law on hospital reform and patients, health and territor...

Explainable machine learning to identify risk factors for unplanned hospital readmissions in Nova Scotian hospitals.

OBJECTIVE: A report from the Canadian Institute for Health Information found unplanned hospital read...

Post-Anesthesia Care Unit (PACU) readiness predictions using machine learning: a comparative study of algorithms.

INTRODUCTION: Accurate and timely discharge from the Post-Anesthesia Care Unit (PACU) is essential t...

Assessing the accuracy of the GPT-4 model in multidisciplinary tumor board decision prediction.

PURPOSE: Artificial intelligence models like GPT-4 (OpenAI) have the potential to support clinical d...

Optimizing imaging modalities for sarcoma subtypes in radiation therapy: State of the art.

The choice of imaging modalities is essential in sarcoma management, as different techniques provide...

Perceived Barriers and Facilitators of Use of Artificial Intelligence in Eating Disorder Care: A Commentary on Linardon et al. (2025).

Artificial intelligence (AI) has the potential to revolutionize mental health care, including for ea...

Evaluation and comparison of machine learning algorithms for predicting discharge against medical advice in injured inpatients.

BACKGROUND: Whether the application of machine learning algorithms offers an advantage over logistic...

Explainable SHAP-XGBoost models for pressure injuries among patients requiring with mechanical ventilation in intensive care unit.

pressure injuries are significant concern for ICU patients on mechanical ventilation. Early predicti...

Innovative Technologies for Smarter and Efficient Operating Room Scheduling.

An optimized scheduling system for surgical procedures is considered fundamental for maximizing hosp...

Development and validation of a machine learning-based nomogram for predicting prognosis in lung cancer patients with malignant pleural effusion.

Malignant pleural effusion (MPE) is a common complication in patients with advanced lung cancer, sig...

Can Artificial Intelligence Software be Utilised for Thyroid Multi-Disciplinary Team Outcomes?

OBJECTIVES: ChatGPT is one of the most publicly available artificial intelligence (AI) softwares. Ea...

Using Machine Learning to Identify Social Determinants of Health that Impact Discharge Disposition for Hospitalized Patients.

OBJECTIVE: To identify self-reported social determinants of health (SDOH) among hospitalized patient...

Multidisciplinary characterization of embarrassment through behavioral and acoustic modeling.

Embarrassment is a social emotion that shares many characteristics with social anxiety (SA). Most pe...

Multimodal treatment of colorectal liver metastases: Where are we? Current strategies and future perspectives.

Despite the continued high prevalence of colorectal cancer in the Western world, recent years have w...

Harnessing Electronic Health Records and Artificial Intelligence for Enhanced Cardiovascular Risk Prediction: A Comprehensive Review.

Electronic health records (EHR) have revolutionized cardiovascular disease (CVD) research by enablin...

Development and validation of machine learning-based prediction model for outcome of cardiac arrest in intensive care units.

Cardiac arrest (CA) poses a significant global health challenge and often results in poor prognosis....

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