Prevention

Preoperative submaximal cardiopulmonary exercise testing and its association with early postoperative complications.

BACKGROUND: Early postoperative complication risk prediction would enhance perioperative surveillance and resource allocation. Reports have described brief submaximal cardiopulmonary exercise testing (CPET) for the routine assessment of cardiopulmonary disease. Compared with conventional CPET, it can be performed in 6 min and is used to predict peak CPET measurements. We aimed to determine whether...

Microfinance institutions failure prediction in emerging countries, a machine learning approach.

This study is about what matters: predicting when microfinance institutions might fail, especially in places where financial stability is closely linked to economic inclusion. The challenge? Creating something practical and usable. The Adjusted Gross Granular Model (ARGM) model comes here. It combines clever techniques, such as granular computing and machine learning, to handle messy and imbalance...

Improved food image recognition by leveraging deep learning and data-driven methods with an application to Central Asian Food Scene.

The burden of diet-related diseases is high in Central Asia. In recent years, the field of food computing has gained prominence due to advancements in...

Artificial intelligence models utilize lifestyle factors to predict dry eye related outcomes.

The purpose of this study is to examine and interpret machine learning models that predict dry eye (DE)-related clinical signs, subjective symptoms, a...

Physiological and morphological impact of physical activity and nutritional interventions to offset disuse-induced skeletal muscle atrophy.

Skeletal muscle tissue acts as a functional unit for physical movements, energy metabolism, thermogenesis, and metabolic homeostasis. In this literatu...

Unique Microbial Characterisation of Oesophageal Squamous Cell Carcinoma Patients with Different Dietary Habits Based on Light Gradient Boosting Machine Learning Classifier.

: The microbiome plays an important role in cancer, but the relationship between dietary habits and the microbiota in oesophageal squamous cell carcin...

Assessing the cardioprotective effects of exercise in APOE mouse models using deep learning and photon-counting micro-CT.

BACKGROUND: The allelic variations of the apolipoprotein E (APOE) gene play a critical role in regulating lipid metabolism and significantly impact ca...

Classroom network structure learning engagement and parallel temporal attention LSTM based knowledge tracing.

In order to accurately assess the students' learning process and the cognitive state of knowledge points in smart classroom. A classroom network struc...

Design of an Interactive Exercise and Leisure System for the Elderly Integrating Artificial Intelligence and Motion-Sensing Technology.

In response to the global trend of population aging, the issue of providing elderly individuals suitable leisure and entertainment has become increasi...

A personalized recommendation algorithm for English exercises incorporating fuzzy cognitive models and multiple attention mechanisms.

In the era of digital education, the rapid growth and disordered distribution of learning resources present new challenges for online learning. Howeve...

Transforming physical fitness and exercise behaviors in adolescent health using a life log sharing model.

INTRODUCTION: This study investigates the potential of a deep learning-based Life Log Sharing Model (LLSM) to enhance adolescent physical fitness and ...

Contemporary digital marketing techniques used in unhealthy food campaigns targeting young people.

The digital marketing of unhealthy foods and non-alcoholic beverages has a detrimental impact on children's eating behaviours, leading to adverse diet...

An innovative model based on machine learning and fuzzy logic for tracking lower limb exercises in stroke patients.

Rehabilitation after a stroke is vital for regaining functional abilities. However, a shortage of rehabilitation professionals leads to many patients ...

Improving machine learning models through explainable AI for predicting the level of dietary diversity among Ethiopian preschool children.

BACKGROUND: Child nutrition in Ethiopia is a significant concern, particularly for preschool-aged children. Children must have a varied diet to ensure...

Development of an artificial intelligence-enhanced warfarin interaction checker platform.

Warfarin is a common anticoagulant drug for thrombo-prophylaxis in stroke and venous thromboembolism, which has many advantages but also some disadvan...

Mitigation of the toxic effects of nitrite: Role and mechanism of isoleucine in mitigating mitochondrial DNA leakage-induced inflammation in grass carp (Ctenopharyngodon idella) under nitrite exposure.

The physiological and growth processes of fish are closely associated with their surrounding environment. This study investigated the role and underly...

Learning from the machine: is diabetes in adults predicted by lifestyle variables? A retrospective predictive modelling study of NHANES 2007-2018.

OBJECTIVES: This study aimed to compare the performance of five machine learning algorithms to predict diabetes mellitus based on lifestyle factors (d...

NutriRAG: Unleashing the Power of Large Language Models for Food Identification and Classification through Retrieval Methods.

OBJECTIVE: This study explores the use of advanced Natural Language Processing (NLP) techniques to enhance food classification and dietary analysis us...

Improving traceability and quality control in the red-meat industry through computer vision-driven physical meat feature tracking.

Current traceability systems rely heavily on external markers which can be altered or tampered with. We hypothesized that the unique intramuscular fat...

Evaluation of artificial intelligence robot's knowledge and reliability on dental implants and peri-implant phenotype.

The aim of this study was to evaluate the reliability and quality of information generated by ChatGPT regarding dental implants and peri-implant pheno...