AIMC Topic: United States

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Machine learning enables legal risk assessment in internet healthcare using HIPAA data.

Scientific reports
This study explores how artificial intelligence technologies can enhance the regulatory capacity for legal risks in internet healthcare based on a machine learning (ML) analytical framework and utilizes data from the health insurance portability and ...

METS-VF as a novel predictor of gallstones in U.S. adults: a cross-sectional analysis (NHANES 2017-2020).

BMC gastroenterology
BACKGROUND AND AIMS: Obesity is a well-established risk factor for gallstone formation, but traditional anthropometric measures (e.g., BMI, waist circumference) inadequately assess metabolically active visceral adiposity. The novel Metabolic Score fo...

Association between atherogenic index of plasma and hypertension combined with diabetes mellitus in United States adults: an analysis of the NHANES surveys from 2011 to 2016.

Journal of health, population, and nutrition
INTRODUCTION: Observational studies have indicated that individuals with hypertension (HTN) and diabetes mellitus (DM) tend to exhibit elevated plasma atherogenic index of plasma (AIP), defined as log (triglyceride [TG]/high-density lipoprotein chole...

The application and predictive value of the weight-adjusted-waist index in BC prevalence assessment: a comprehensive statistical and machine learning analysis using NHANES data.

BMC cancer
BACKGROUND: Obesity is a known risk factor for breast cancer (BC), but conventional metrics such as body mass index (BMI) may insufficiently capture central adiposity. The weight-adjusted waist index (WWI) has emerged as a potentially superior anthro...

AI generated annotations for Breast, Brain, Liver, Lungs, and Prostate cancer collections in the National Cancer Institute Imaging Data Commons.

Scientific data
The Artificial Intelligence in Medical Imaging (AIMI) initiative aims to enhance the National Cancer Institute's (NCI) Image Data Commons (IDC) by releasing fully reproducible nnU-Net models, along with AI-assisted segmentation for cancer radiology i...

Relative importance of socioecological domains to predicting opioid-involved mortality.

PloS one
BACKGROUND: The opioid crisis in the United States is a complex issue with interconnected factors that lead to opioid misuse and opioid-involved mortality. This study assessed the relative importance of different risk factor domains in predicting fat...

Machine learning driven diabetes care using predictive-prescriptive analytics for personalized medication prescription.

Scientific reports
The increasing prevalence of type 2 diabetes (T2D) is a significant health concern worldwide. Effective and personalized treatment strategies are essential for improving patient outcomes and reducing healthcare costs. Machine learning (ML) has the po...

Evaluating the Usability, Technical Performance, and Accuracy of Artificial Intelligence Scribes for Primary Care: Competitive Analysis.

JMIR human factors
BACKGROUND: Primary care providers (PCPs) face significant burnout due to increasing administrative and documentation demands, contributing to job dissatisfaction and impacting care quality. Artificial intelligence (AI) scribes have emerged as potent...

Clinical characteristics and CKD care delivery in African American and American Indian or Alaska Native patients: A real-world cohort study.

BMC nephrology
BACKGROUND: Racially minoritized populations in the United States (US), notably African American (AA) and American Indian/Alaska Native (AI/AN), experience disproportionately higher rates of chronic kidney disease (CKD), diabetes, and hypertension co...

Baltic dry index forecast using financial market data: Machine learning methods and SHAP explanations.

PloS one
The Baltic Dry Index (BDI) is a critical benchmark for assessing freight rates and chartering activity in the global shipping market. This study forecasts the BDI using diverse financial data, including commodities, currencies, stock markets, and vol...