Hospital-Based Medicine

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

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Machine Learning in Electroconvulsive Therapy: A Systematic Review.

Despite years of research, we are still not able to reliably predict who might benefit from electroc...

Analysis of Cerebral CT Based on Supervised Machine Learning as a Predictor of Outcome After Out-of-Hospital Cardiac Arrest.

BACKGROUND AND OBJECTIVES: In light of limited intensive care capacities and a lack of accurate prog...

Patient-centered radiology reports with generative artificial intelligence: adding value to radiology reporting.

The purposes were to assess the efficacy of AI-generated radiology reports in terms of report summar...

The Future Role of Radiologists in the Artificial Intelligence-Driven Hospital.

Increasing population and healthcare costs make changes in the healthcare system necessary. This art...

Predictive approach for liberation from acute dialysis in ICU patients using interpretable machine learning.

Renal recovery following dialysis-requiring acute kidney injury (AKI-D) is a vital clinical outcome ...

Towards abundant intelligences: Considerations for Indigenous perspectives in adopting artificial intelligence technology.

Artificial Intelligence (AI) applications in healthcare are evolving rapidly. The integration of AI ...

Artificial intelligence in perinatal mental health research: A scoping review.

The intersection of Artificial Intelligence (AI) and perinatal mental health research presents promi...

Dissatisfaction-considered waiting time prediction for outpatients with interpretable machine learning.

Long waiting time in outpatient departments is a crucial factor in patient dissatisfaction. We aim t...

Predicting treatment resistance in schizophrenia patients: Machine learning highlights the role of early pathophysiologic features.

Detecting patients with a high-risk profile for treatment-resistant schizophrenia (TRS) can be benef...

Clinicosocial determinants of hospital stay following cervical decompression: A public healthcare perspective and machine learning model.

OBJECTIVE: Post-operative length of hospital stay (LOS) is a valuable measure for monitoring quality...

Ensemble machine learning for predicting in-hospital mortality in Asian women with ST-elevation myocardial infarction (STEMI).

The accurate prediction of in-hospital mortality in Asian women after ST-Elevation Myocardial Infarc...

Comparative analysis of machine learning versus traditional method for early detection of parental depression symptoms in the NICU.

INTRODUCTION: Neonatal intensive care unit (NICU) admission is a stressful experience for parents. N...

Predicting medical waste generation and associated factors using machine learning in the Kingdom of Bahrain.

Effective planning and managing medical waste necessitate a crucial focus on both the public and pri...

Neural topic models with survival supervision: Jointly predicting time-to-event outcomes and learning how clinical features relate.

We present a neural network framework for learning a survival model to predict a time-to-event outco...

Predicting 1 year readmission for heart failure: A comparative study of machine learning and the LACE index.

AIMS: There is a lack of tools for accurately identifying the risk of readmission for heart failure ...

A new machine learning model to predict the prognosis of cardiogenic brain infarction.

Cardiogenic cerebral infarction (CCI) is a disease in which the blood supply to the blood vessels in...

Prediction of naloxone dose in opioids toxicity based on machine learning techniques (artificial intelligence).

BACKGROUND: Treatment management for opioid poisoning is critical and, at the same time, requires sp...

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