Hospital-Based Medicine

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

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Readability of Orthopaedic Patient Educational Material: An artificial intelligence application.

BACKGROUND: This study aims to determine the efficacy of the use of artificial intelligence (AI) in ...

Comparing neural language models for medical concept representation and patient trajectory prediction.

Effective representation of medical concepts is crucial for secondary analyses of electronic health ...

Intelligent risk stratification of hypertension based on ambulatory blood pressure monitoring and machine learning algorithms.

. Risk stratification of hypertension plays a crucial role in the treatment decisions and medication...

Validation of patient-specific deep learning markerless lung tumor tracking aided by 4DCBCT.

. Tracking tumors with multi-leaf collimators and x-ray imaging can be a cost-effective motion manag...

Development and validation of an interpretable machine learning model for predicting in-hospital mortality for ischemic stroke patients in ICU.

BACKGROUND: Timely and accurate outcome prediction is essential for clinical decision-making for isc...

Dynamic HRV Monitoring and Machine Learning Predict NYHA Improvements in Acute Heart Failure Patients.

Heart failure (HF) is marked by significant morbidity, mortality, and readmission rates, highlightin...

Using Natural Language Processing in the LACE Index Scoring Tool to Predict Unplanned Trauma and Surgical Readmissions in South Africa.

BACKGROUND: Unplanned and potentially avoidable readmission within 30 days post discharge is a major...

Harnessing Artificial Intelligence for Precision Diagnosis and Treatment of Triple Negative Breast Cancer.

Triple-Negative Breast Cancer (TNBC) is a highly aggressive subtype of breast cancer (BC) characteri...

Predictive value of machine learning for in-hospital mortality risk in acute myocardial infarction: A systematic review and meta-analysis.

BACKGROUND: Machine learning (ML) models have been constructed to predict the risk of in-hospital mo...

Applying Robotic Process Automation to Monitor Business Processes in Hospital Information Systems: Mixed Method Approach.

BACKGROUND: Electronic medical records (EMRs) have undergone significant changes due to advancements...

Leveraging Artificial Intelligence to Reduce Neuroscience ICU Length of Stay.

GOAL: Efficient patient flow is critical at Tampa General Hospital (TGH), a large academic tertiary ...

Automatic detecting multiple bone metastases in breast cancer using deep learning based on low-resolution bone scan images.

Whole-body bone scan (WBS) is usually used as the effective diagnostic method for early-stage and co...

RTGN: Robust Traditional Chinese Medicine Graph Networks for Patient Similarity Learning.

Traditional Chinese Medicine (TCM) boasts a long history and a unique diagnostic and therapeutic par...

Predicting Readmission Among High-Risk Discharged Patients Using a Machine Learning Model With Nursing Data: Retrospective Study.

BACKGROUND: Unplanned readmissions increase unnecessary health care costs and reduce the quality of ...

Unlocking new frontiers in epilepsy through AI: From seizure prediction to personalized medicine.

Artificial intelligence (AI) is revolutionizing epilepsy care by advancing seizure detection, enhanc...

An Efficient Approach for Detection of Various Epileptic Waves Having Diverse Forms in Long Term EEG Based on Deep Learning.

EEG is the most powerful tool for epilepsy discharge detection in brain. Visual evaluation is hard i...

Machine Learning-Based Prediction of Early Complications Following Surgery for Intestinal Obstruction: Multicenter Retrospective Study.

BACKGROUND: Early complications increase in-hospital stay and mortality after intestinal obstruction...

Machine learning for the rElapse risk eValuation in acute biliary pancreatitis: The deep learning MINERVA study protocol.

BACKGROUND: Mild acute biliary pancreatitis (MABP) presents significant clinical and economic challe...

AI-powered prostate cancer detection: a multi-centre, multi-scanner validation study.

OBJECTIVES: Multi-centre, multi-vendor validation of artificial intelligence (AI) software to detect...

Risk factors and an interpretability tool of in-hospital mortality in critically ill patients with acute myocardial infarction.

OBJECTIVE: We aim to develop and validate an interpretable machine-learning model that can provide c...

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