AIMC Topic: Aged

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Explainable machine learning identifies a polygenic risk score as a key predictor of pancreatic cancer risk in the UK Biobank.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND: Predicting the risk of developing pancreatic ductal adenocarcinoma (PDAC) is of paramount importance, given its high mortality rate. Current PDAC risk prediction models rely on a limited number of variables, do not include genetics, and h...

ChatGPT vs. surgeons on pancreatic cancer queries: accuracy & empathy evaluated by patients and experts.

HPB : the official journal of the International Hepato Pancreato Biliary Association
BACKGROUND: Artificial intelligence (AI) offers potential support in patient-clinician interactions, but its impact on such communication remains unexplored.

A Machine learning classification framework using fused fractal property feature vectors for Alzheimer's disease diagnosis.

Brain research
Alzheimer's disease (AD) profoundly affects brain tissue and network structures. Analyzing the topological properties of these networks helps to understand the progression of the disease. Most studies focus on single-scale brain networks, but few add...

Comparative Analysis of Nomogram and Machine Learning Models for Predicting Axillary Lymph Node Metastasis in Early-Stage Breast Cancer: A Study on Clinically and Ultrasound-Negative Axillary Cases Across Two Centers.

Ultrasound in medicine & biology
OBJECTIVE: Early and accurate prediction of axillary lymph node metastasis (ALNM) is crucial in determining appropriate treatment strategies for patients with early-stage breast cancer. The aim of this study was to evaluate the efficacy of radiomic f...

Machine learning in predicting cauda equina imaging outcomes- a solution to the problem.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: Cauda Equina Syndrome (CES) is a rare surgical emergency. The implications for loss of quality of life through delayed management are high, though no clinical symptom is pathognomonic in its diagnosis. We describe how machine learning based ...

Assessing Locomotive Syndrome Through Instrumented Five-Time Sit-to-Stand Test and Machine Learning.

Sensors (Basel, Switzerland)
Locomotive syndrome (LS) refers to a condition where individuals face challenges in performing activities of daily living. Early detection of such deterioration is crucial to reduce the need for nursing care. The Geriatric Locomotive Function Scale (...

Exploring the risk factors and clustering patterns of periodontitis in patients with different subtypes of diabetes through machine learning and cluster analysis.

Acta odontologica Scandinavica
AIM: To analyse the risk factors contributing to the prevalence of periodontitis among clusters of patients with diabetes and to examine the clustering patterns of clinical blood biochemical indicators.

Machine learning based metabolomic and genetic profiles for predicting multiple brain phenotypes.

Journal of translational medicine
BACKGROUND: It is unclear regarding the association between metabolomic state/genetic risk score(GRS) and brain volumes and how much of variance of brain volumes is attributable to metabolomic state or GRS.

Application of machine learning in breast cancer survival prediction using a multimethod approach.

Scientific reports
Breast cancer is one of the most prevalent cancers with an increasing trend in both incidence and mortality rates in Iran. Survival analysis is a pivotal measure in setting appropriate care plans.  To the best of our knowledge, this study is pioneeri...