AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Risk Assessment

Showing 61 to 70 of 2312 articles

Clear Filters

Machine learning assessment of zoonotic potential in avian influenza viruses using PB2 segment.

BMC genomics
BACKGROUND: Influenza A virus (IAV) is a major global health threat, causing seasonal epidemics and occasional pandemics. Particularly, Influenza A viruses from avian species pose significant zoonotic threats, with PB2 adaptation serving as a critica...

Exploring the Impact of PA and Sedentary Behavior on Gout Risk in Hyperuricemia: Insights From Machine Learning and SHAP Analysis.

International journal of rheumatic diseases
BACKGROUND: Individuals with hyperuricemia (HUA) are widely recognized as being at increased risk for gout. This study aimed to investigate how physical activity (PA) duration and sedentary duration impact gout risk in individuals with HUA and to dev...

Development and validation of a machine learning risk prediction model for asthma attacks in adults in primary care.

NPJ primary care respiratory medicine
Primary care consultations provide an opportunity for patients and clinicians to assess asthma attack risk. Using a data-driven risk prediction tool with routinely collected health records may be an efficient way to aid promotion of effective self-ma...

Preoperative lymph node metastasis risk assessment in invasive micropapillary carcinoma of the breast: development of a machine learning-based predictive model with a web-based calculator.

World journal of surgical oncology
BACKGROUND: Invasive micropapillary carcinoma (IMPC) is a rare subtype of breast cancer characterized by a high risk of lymph node metastasis (LNM). The study aimed to identify predictors of LNM and to develop a machine learning (ML)-based risk predi...

Explainable machine learning algorithm to predict cardiovascular event in patients undergoing peritoneal dialysis.

BMC medical informatics and decision making
OBJECTIVE: To compare the performance of predictive models for cardiovascular event (CVE) in patients undergoing peritoneal dialysis (PD) based on machine learning algorithm and Cox proportional hazard regression.

Development of explainable artificial intelligence based machine learning model for predicting 30-day hospital readmission after renal transplantation.

BMC nephrology
BACKGROUND: Hospital readmission following renal transplantation significantly impacts patient outcomes and healthcare resources. While machine learning approaches offer promising solutions for risk prediction, their clinical application often lacks ...

A machine learning model for predicting acute respiratory distress syndrome risk in patients with sepsis using circulating immune cell parameters: a retrospective study.

BMC infectious diseases
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a severe complication associated with a high mortality rate in patients with sepsis. Early identification of patients with sepsis at high risk of developing ARDS is crucial for timely interven...

Estimating individualized effectiveness of receiving successful recanalization for ischemic stroke cases using machine learning techniques.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: Directly measuring the causal effect of mechanical thrombectomy (MT) for each ischemic stroke patient remains challenging, as it is impossible to observe the outcomes for both with and without successful recanalization in the same individ...

Exploring trade-offs in equitable stroke risk prediction with parity-constrained and race-free models.

Artificial intelligence in medicine
A recent analysis of common stroke risk prediction models showed that performance differs between Black and White subgroups, and that applying standard machine learning methods does not reduce these disparities. There have been calls in the clinical ...