AI Medical Compendium Topic

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

Life Style

Showing 21 to 30 of 67 articles

Clear Filters

Comparative analysis of machine learning models for efficient low back pain prediction using demographic and lifestyle factors.

Journal of back and musculoskeletal rehabilitation
BACKGROUND: Low back pain (LBP) is one of the most frequently occurring musculoskeletal disorders, and factors such as lifestyle as well as individual characteristics are associated with LBP.

Machine Learning Approach to Study Social Determinants of Chronic Illness in India: A Comparative Analysis.

Indian journal of public health
BACKGROUND: Several studies on noncommunicable diseases (NCDs) have been carried out worldwide, the basis of most of which is the identification of risk factors-modifiable (or behavioral) and metabolic. Majority of the NCDs are due to sociodemographi...

A Data-Driven Approach to Predicting Recreational Activity Participation Using Machine Learning.

Research quarterly for exercise and sport
With the popularity of recreational activities, the study aimed to develop prediction models for recreational activity participation and explore the key factors affecting participation in recreational activities. A total of 12,712 participants, exc...

AI-based digital pathology provides newer insights into lifestyle intervention-induced fibrosis regression in MASLD: An exploratory study.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND AND AIMS: Lifestyle intervention is the mainstay of therapy for metabolic dysfunction-associated steatohepatitis (MASH), and liver fibrosis is a key consequence of MASH that predicts adverse clinical outcomes. The placebo response plays a ...

Predicting dyslipidemia incidence: unleashing machine learning algorithms on Lifestyle Promotion Project data.

BMC public health
BACKGROUND: Dyslipidemia, characterized by variations in plasma lipid profiles, poses a global health threat linked to millions of deaths annually.

The prediction of semen quality based on lifestyle behaviours by the machine learning based models.

Reproductive biology and endocrinology : RB&E
PURPOSE: To find the machine learning (ML) method that has the highest accuracy in predicting the semen quality of men based on basic questionnaire data about lifestyle behavior.

An artificial intelligence tool to assess the risk of severe mental distress among college students in terms of demographics, eating habits, lifestyles, and sport habits: an externally validated study using machine learning.

BMC psychiatry
BACKGROUND: Precisely estimating the probability of mental health challenges among college students is pivotal for facilitating timely intervention and preventative measures. However, to date, no specific artificial intelligence (AI) models have been...

Digital therapeutics in hypertension: How to make sustainable lifestyle changes.

Journal of clinical hypertension (Greenwich, Conn.)
Various digital therapeutic products have been validated and approved since 2017. They have demonstrated efficacy and safety as a new therapeutic modality in various disorders or conditions. Hypertension is a common but serious condition that can be ...

Exploring key factors influencing depressive symptoms among middle-aged and elderly adult population: A machine learning-based method.

Archives of gerontology and geriatrics
OBJECTIVE: This paper aims to investigate the key factors, including demographics, socioeconomics, physical well-being, lifestyle, daily activities and loneliness that can impact depressive symptoms in the middle-aged and elderly population using mac...

Predicting non-responders to lifestyle intervention in prediabetes: a machine learning approach.

European journal of clinical nutrition
BACKGROUND: The clinical care process for people with prediabetes starts with lifestyle intervention, often escalating to more intense treatment due to the low success rate of the first-line intervention. Clinicians lack clear guidelines on which pat...