AIMC Topic: Risk Factors

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A machine learning-based risk prediction model for diabetic oral ulceration.

BMC oral health
BACKGROUND: Diabetic oral ulceration (DOU) is a prevalent and debilitating complication among diabetic patients, significantly impairing their quality of life and imposing substantial economic burdens. Studies indicate that over 90% of diabetic patie...

Machine learning prediction model with shap interpretation for chronic bronchitis risk assessment based on heavy metal exposure: a nationally representative study.

BMC pulmonary medicine
BACKGROUND: Chronic bronchitis (CB), as a core precursor of Chronic Obstructive Pulmonary Disease (COPD), is crucial for global disease burden prevention and control. Although the association between heavy metal exposure and respiratory damage has be...

Machine learning in colorectal polyp surveillance: A paradigm shift in post-endoscopic mucosal resection follow-up.

World journal of gastroenterology
Colorectal cancer remains a major health concern, with colorectal polyps as key precursors. Endoscopic mucosal resection (EMR) is a common treatment, but recurrence rates remain high. Traditional surveillance strategies rely on polyp characteristics ...

Patient research priorities in melanoma: a national qualitative interview study.

The British journal of dermatology
BACKGROUND: Outcomes for advanced melanoma have improved following the advent of immunotherapy and targeted therapy. This heralds a need for reconsideration of future research agendas. Patients can - and are keen to - help identify and prioritize res...

Comparing interpretable machine learning models for fall risk in middle-aged and older adults with and without pain.

Scientific reports
Pain is common in middle-aged and older adults, has also been identified as a fall risk factor, whereas the mechanism of falls in pain is unclear. This study included 13,074 middle-aged and older adults from the China health and retirement longitudin...

Sociodemographic Profile of People with Diagnosed Pancreatic Cancer in the UK: Retrospective Sentinel Network Cohort Study.

Studies in health technology and informatics
Pancreatic cancer is a devasting disease which is an increasing cause of cancer mortality. The aim of this study was to characterise, using descriptive statistics, the sociodemographic, risk and clinical characteristics of who develops pancreatic can...

An Interpretable Model for Predicting Acute Myocardial Infarction in Distinct Patient Profiles.

Studies in health technology and informatics
INTRODUCTION: Acute myocardial infarction (AMI) is highly prevalent (3.8% in developed countries), affecting heterogenous populations, and can be influenced by varied factors, including demographics, clinical risk factors, and comorbidities. Identify...

Machine learning for predicting all-cause mortality of metabolic dysfunction-associated fatty liver disease: a longitudinal study based on NHANES.

BMC gastroenterology
BACKGROUND: The mortality burden of metabolic dysfunction-associated fatty liver disease (MAFLD) is rising, making it crucial to predict mortality and identify the factors influencing it. While advanced machine learning algorithms are gaining recogni...

In-depth analysis of the risk factors for persistent severe acute respiratory syndrome coronavirus 2 infection and construction of predictive models: an exploratory research study.

BMC infectious diseases
BACKGROUND: Persistent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection differs from long coronavirus disease (COVID-19) (acute symptoms ≥ 12 weeks post-clearance). The Omicron BA.5 variant has a shorter median clearance time (1...