AIMC Topic: Risk Factors

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A machine learning algorithm-based predictive model for pressure injury risk in emergency patients: A prospective cohort study.

International emergency nursing
OBJECTIVES: To construct pressure injury risk prediction models for emergency patients based on different machine learning algorithms, to optimize the best model, and to provide a suitable assessment tool for preventing the occurrence of pressure inj...

Deep learning-based prediction of post-pancreaticoduodenectomy pancreatic fistula.

Scientific reports
Postoperative pancreatic fistula is a life-threatening complication with an unmet need for accurate prediction. This study was aimed to develop preoperative artificial intelligence-based prediction models. Patients who underwent pancreaticoduodenecto...

White matter brain age as a biomarker of cerebrovascular burden in the ageing brain.

European archives of psychiatry and clinical neuroscience
As the brain ages, it almost invariably accumulates vascular pathology, which differentially affects the cerebral white matter. A rich body of research has investigated the link between vascular risk factors and the brain. One of the less studied que...

An advanced machine learning method for simultaneous breast cancer risk prediction and risk ranking in Chinese population: A prospective cohort and modeling study.

Chinese medical journal
BACKGROUND: Breast cancer (BC) risk-stratification tools for Asian women that are highly accurate and can provide improved interpretation ability are lacking. We aimed to develop risk-stratification models to predict long- and short-term BC risk amon...

Dietary patterns associated with the incidence of hypertension among adult Japanese males: application of machine learning to a cohort study.

European journal of nutrition
PURPOSE: The previous studies that examined the effectiveness of unsupervised machine learning methods versus traditional methods in assessing dietary patterns and their association with incident hypertension showed contradictory results. Consequentl...

Machine learning application identifies plasma markers for proteinuria in metastatic colorectal cancer patients treated with Bevacizumab.

Cancer chemotherapy and pharmacology
BACKGROUND AND OBJECTIVES: Proteinuria is a common complication after the application of bevacizumab therapy in patients with metastatic colorectal cancer, and severe proteinuria can lead to discontinuation of the drug. There is a lack of sophisticat...

Prevalence and risk factors analysis of postpartum depression at early stage using hybrid deep learning model.

Scientific reports
Postpartum Depression Disorder (PPDD) is a prevalent mental health condition and results in severe depression and suicide attempts in the social community. Prompt actions are crucial in tackling PPDD, which requires a quick recognition and accurate a...

Biochemical implications of robotic surgery: a new frontier in the operating room.

Journal of robotic surgery
Robotic surgery represents a milestone in surgical procedures, offering advantages such as less invasive methods, elimination of tremors, scaled motion, and 3D visualization. This in-depth analysis explores the complex biochemical effects of robotic ...