AI Medical Compendium Topic

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

Risk Assessment

Showing 271 to 280 of 2320 articles

Clear Filters

A multi-model machine learning framework for breast cancer risk stratification using clinical and imaging data.

Journal of X-ray science and technology
PurposeThis study presents a comprehensive machine learning framework for assessing breast cancer malignancy by integrating clinical features with imaging features derived from deep learning.MethodsThe dataset included 1668 patients with documented b...

Machine Learning Model for Risk Stratification of Papillary Thyroid Carcinoma Based on Radiopathomics.

Academic radiology
RATIONALE AND OBJECTIVES: This study aims to develop a radiopathomics model based on preoperative ultrasound and fine-needle aspiration cytology (FNAC) images to enable accurate, non-invasive preoperative risk stratification for patients with papilla...

Statistical models versus machine learning approach for competing risks in proctological surgery.

Updates in surgery
Clinical risk prediction models are ubiquitous in many surgical domains. The traditional approach to develop these models involves the use of regression analysis. Machine learning algorithms are gaining in popularity as an alternative approach for pr...

Machine Learning to Predict Mortality in Older Patients With Cancer: Development and External Validation of the Geriatric Cancer Scoring System Using Two Large French Cohorts.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology
PURPOSE: Establishing an accurate prognosis remains challenging in older patients with cancer because of the population's heterogeneity and the current predictive models' reduced ability to capture the complex interactions between oncologic and geria...

The association of lifestyle with cardiovascular and all-cause mortality based on machine learning: a prospective study from the NHANES.

BMC public health
BACKGROUND: Lifestyle and cardiovascular mortality and all-cause mortality have been exhaustively explored by traditional methods, but the advantages of machine learning (ML) over traditional methods may lead to different or more precise conclusions....

Random Survival Forest Machine Learning for the Prediction of Cardiovascular Events Among Patients With a Measured Lipoprotein(a) Level: A Model Development Study.

Circulation. Genomic and precision medicine
BACKGROUND: Established risk models may not be applicable to patients at higher cardiovascular risk with a measured Lp(a) (lipoprotein[a]) level, a causal risk factor for atherosclerotic cardiovascular disease.

Prognosis modelling of adverse events for post-PCI treated AMI patients based on inflammation and nutrition indexes.

BMC cardiovascular disorders
OBJECTIVE: This study aimed to evaluate the predictive performance of inflammatory and nutritional indices for adverse cardiovascular events (ACE) in patients with acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI) using...

Leveraging artificial intelligence to detect ethical concerns in medical research: a case study.

Journal of medical ethics
BACKGROUND: Institutional review boards (IRBs) have been criticised for delays in approvals for research proposals due to inadequate or inexperienced IRB staff. Artificial intelligence (AI), particularly large language models (LLMs), has significant ...

Multimodal integration using a machine learning approach facilitates risk stratification in HR+/HER2- breast cancer.

Cell reports. Medicine
Hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer is the most common type of breast cancer, with continuous recurrence remaining an important clinical issue. Current relapse predictive models in H...

Death risk prediction model for patients with non-traumatic intracerebral hemorrhage.

BMC medical informatics and decision making
BACKGROUND: This study aimed to assess the risk of death from non-traumatic intracerebral hemorrhage (ICH) using a machine learning model.