AIMC Topic: Risk Factors

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AI-powered prediction of HCC recurrence after surgical resection: Personalised intervention opportunities using patient-specific risk factors.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND: Hepatocellular carcinoma (HCC) recurrence following surgical resection remains a significant clinical challenge, necessitating reliable predictive models to guide personalised interventions. In this study, we sought to harness the power o...

Development and validation of radiology-clinical statistical and machine learning model for stroke-associated pneumonia after first intracerebral haemorrhage.

BMC pulmonary medicine
BACKGROUND: Society is burdened with stroke-associated pneumonia (SAP) after intracerebral haemorrhage (ICH). Cerebral small vessel disease (CSVD) complicates clinical manifestations of stroke. In this study, we redefined the CSVD burden score and in...

Machine Learning Predicts Unplanned Care Escalations for Post-Anesthesia Care Unit Patients during the Perioperative Period: A Single-Center Retrospective Study.

Journal of medical systems
BACKGROUND:  Despite low mortality for elective procedures in the United States and developed countries, some patients have unexpected care escalations (UCE) following post-anesthesia care unit (PACU) discharge. Studies indicate patient risk factors ...

A stacking ensemble model for predicting the occurrence of carotid atherosclerosis.

Frontiers in endocrinology
BACKGROUND: Carotid atherosclerosis (CAS) is a significant risk factor for cardio-cerebrovascular events. The objective of this study is to employ stacking ensemble machine learning techniques to enhance the prediction of CAS occurrence, incorporatin...

Risk prediction of kalaemia disturbance and acute kidney injury after total knee arthroplasty: use of a machine learning algorithm.

Orthopaedics & traumatology, surgery & research : OTSR
INTRODUCTION: Total knee arthroplasty (TKA) is a procedure associated with risks of electrolyte and kidney function disorders, which are rare but can lead to serious complications if not correctly identified. A routine check-up is very often carried ...

Interpretable machine learning models for detecting peripheral neuropathy and lower extremity arterial disease in diabetics: an analysis of critical shared and unique risk factors.

BMC medical informatics and decision making
BACKGROUND: Diabetic peripheral neuropathy (DPN) and lower extremity arterial disease (LEAD) are significant contributors to diabetic foot ulcers (DFUs), which severely affect patients' quality of life. This study aimed to develop machine learning (M...

Constructing prediction models and analyzing factors in suicidal ideation using machine learning, focusing on the older population.

PloS one
Suicide among the older population is a significant public health concern in South Korea. As the older individuals have long considered suicide before committing suicide trials, it is important to analyze the suicidal ideation that precedes the suici...

Application of a machine learning and optimization method to predict patellofemoral instability risk factors in children and adolescents.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: Conservative treatment remains the standard approach for first-time patellar dislocations. While risk factors for patellofemoral instability, a common paediatric injury, are well-established in adults, data concerning the progression of paed...