Primary Care

Perceptions and Profiles of Young People Regarding Spa Tourism: A Comparative Study of Students from Granada and Aachen Universities.

Spa tourism has undergone important changes in recent decades, actively embracing wellness and wellbeing. However, this transition is taking place in different ways in Europe, and this has led to varying perceptions of thermalism that have little to do with its original conception. The main aim of this study was to analyse current perceptions of spa tourism amongst university students, so as to id...

Body fat prediction through feature extraction based on anthropometric and laboratory measurements.

Obesity, associated with having excess body fat, is a critical public health problem that can cause serious diseases. Although a range of techniques for body fat estimation have been developed to assess obesity, these typically involve high-cost tests requiring special equipment. Thus, the accurate prediction of body fat percentage based on easily accessed body measurements is important for assess...

Evolution of hospitalized patient characteristics through the first three COVID-19 waves in Paris area using machine learning analysis.

Characteristics of patients at risk of developing severe forms of COVID-19 disease have been widely described, but very few studies describe their evo...

Artificial intelligence outperforms standard blood-based scores in identifying liver fibrosis patients in primary care.

For years, hepatologists have been seeking non-invasive methods able to detect significant liver fibrosis. However, no previous algorithm using routin...

A Federated Mining Approach on Predicting Diabetes-Related Complications: Demonstration Using Real-World Clinical Data.

Chronic diabetes can lead to microvascular complications, including diabetic eye disease, diabetic kidney disease, and diabetic neuropathy. However, t...

A Study of Social and Behavioral Determinants of Health in Lung Cancer Patients Using Transformers-based Natural Language Processing Models.

Social and behavioral determinants of health (SBDoH) have important roles in shaping people's health. In clinical research studies, especially compara...

Real-time data analysis in health monitoring systems: A comprehensive systematic literature review.

Health monitoring systems (HMSs) capture physiological measurements through biosensors (sensing), obtain significant properties and measures from the ...

Cardiovascular Disease Screening in Women: Leveraging Artificial Intelligence and Digital Tools.

Cardiovascular disease remains the leading cause of death in women. Given accumulating evidence on sex- and gender-based differences in cardiovascular...

Associations Between Different Dietary Vitamins and the Risk of Obesity in Children and Adolescents: A Machine Learning Approach.

BACKGROUNDS: Simultaneous dietary intake of vitamins is considered as a common and real scenario in daily life. However, limited prospective studies h...

Predicting machine's performance record using the stacked long short-term memory (LSTM) neural networks.

PURPOSE: The record of daily quality control (QC) items shows machine performance patterns and potentially provides warning messages for preventive ac...

A Novel Extra Tree Ensemble Optimized DL Framework (ETEODL) for Early Detection of Diabetes.

Diabetes has been recognized as a global medical problem for more than half a century. Patients with diabetes can benefit from the Internet of Things ...

A machine-learning assisted review of the use of habit formation in medication adherence interventions for long-term conditions.

Adherence to medication in long-term conditions is around 50%. The key components of successful interventions to improve medication adherence remain u...

A machine learning-based on-demand sweat glucose reporting platform.

Diabetes is a chronic endocrine disease that occurs due to an imbalance in glucose levels and altering carbohydrate metabolism. It is a leading cause ...

Evaluations of Deep Learning Approaches for Glaucoma Screening Using Retinal Images from Mobile Device.

Glaucoma is a silent disease that leads to vision loss or irreversible blindness. Current deep learning methods can help glaucoma screening by extendi...

Deep Learning in Human Activity Recognition with Wearable Sensors: A Review on Advances.

Mobile and wearable devices have enabled numerous applications, including activity tracking, wellness monitoring, and human-computer interaction, that...

Machine Learning Techniques in Blood Pressure Management During the Acute Phase of Ischemic Stroke.

BACKGROUND AND PURPOSE: Elevated blood pressure (BP) in acute ischemic stroke is common. A raised BP is related to mortality and disability, yet exces...

Diabetes mellitus risk prediction in the presence of class imbalance using flexible machine learning methods.

BACKGROUND: Early detection and prediction of type two diabetes mellitus incidence by baseline measurements could reduce associated complications in t...

Machine learning-based diagnosis and risk factor analysis of cardiocerebrovascular disease based on KNHANES.

The prevalence of cardiocerebrovascular disease (CVD) is continuously increasing, and it is the leading cause of human death. Since it is difficult fo...

Assessment of medical management in Coronary Type 2 Diabetic patients with previous percutaneous coronary intervention in Spain: A retrospective analysis of electronic health records using Natural Language Processing.

INTRODUCTION AND OBJECTIVES: Patients with type 2 diabetes (T2D) and stable coronary artery disease (CAD) previously revascularized with percutaneous ...

Artificial intelligence-enabled virtual screening of ultra-large chemical libraries with deep docking.

With the recent explosion of chemical libraries beyond a billion molecules, more efficient virtual screening approaches are needed. The Deep Docking (...