Prevention

Milk ladder: Who? When? How? Where? with the lowest risk of reaction.

The milk ladder (ML) approach, which is the gradual reintroduction of the milk allergen from the least allergenic forms to the most allergenic forms into the diet of the patients, has been utilized mostly in non-IgE-mediated but in some countries also in IgE-mediated-CMPA due to its possible benefits which include nutrition, quality of life and tolerance induction. Despite increasing interest, so ...

Explainable exercise recommendation with knowledge graph.

Recommending suitable exercises and providing the reasons for these recommendations is a highly valuable task, as it can significantly improve students' learning efficiency. Nevertheless, the extensive range of exercise resources and the diverse learning capacities of students present a notable difficulty in recommending exercises. Collaborative filtering approaches frequently have difficulties in...

DS-MS-TCN: Otago Exercises Recognition With a Dual-Scale Multi-Stage Temporal Convolutional Network.

The Otago Exercise Program (OEP) represents a crucial rehabilitation initiative tailored for older adults, aimed at enhancing balance and strength. De...

Can people with epilepsy trust AI chatbots for information on physical exercise?

PURPOSE: This study aims to evaluate the similarity, readability, and alignment with current scientific knowledge of responses from AI-based chatbots ...

Identification of ageing-associated gene signatures in heart failure with preserved ejection fraction by integrated bioinformatics analysis and machine learning.

The incidence of heart failure with preserved ejection fraction (HFpEF) increases with the ageing of populations. This study aimed to explore ageing-a...

Parallel development of object recognition in newborn chicks and deep neural networks.

How do newborns learn to see? We propose that visual systems are space-time fitters, meaning visual development can be understood as a blind fitting p...

Physiological and Psychological Differences Between 20% Grade Incline Walking and Level-Grade Jogging at Isocaloric Intensity.

High-incline walking is a relatively new trend with little comparative information. This study compared physiological and psychological differences be...

The factors affecting aerobics athletes' performance using artificial intelligence neural networks with sports nutrition assistance.

This work aims to comprehensively explore the influencing factors of aerobics athletes' performance by integrating sports nutrition assistance and art...

A hybrid healthy diet recommender system based on machine learning techniques.

Obesity is a chronic disease correlated with numerous risk factors that not only negatively affect all body functions but also increase the chances of...

Machine learning insights into scapular stabilization for alleviating shoulder pain in college students.

Non-specific shoulder pain is a common musculoskeletal condition, especially among college students, and it can have a negative impact on the patient'...

Circulating endothelial progenitor cells and inflammatory markers in type 1 diabetes after an acute session of aerobic exercise.

OBJECTIVE: To determine circulating endothelial progenitor cells (EPC) counts and levels of inflammatory markers in individuals with and without type ...

Validation of artificial intelligence-based application to estimate nutrients in daily meals.

BACKGROUND: Diet modification is a mainstay for the successful management of metabolic syndrome and potentially may reduce the risk of cardiovascular ...

The role of aspirin in preventing gastrointestinal cancers.

Cancer remains an increasing global health issue and is projected to cause 50% of all global deaths by 2050. Gastrointestinal (GI) tract cancers curre...

Molecular tweaking by generative cheminformatics and ligand-protein structures for rational drug discovery.

The purpose of this review is two-fold: (1) to summarize artificial intelligence and machine learning approaches and document the role of ligand-prote...

Adversarial Examples on XAI-Enabled DT for Smart Healthcare Systems.

There have recently been rapid developments in smart healthcare systems, such as precision diagnosis, smart diet management, and drug discovery. These...

Predicting laboratory aspirin resistance in Chinese stroke patients using machine learning models by GP1BA polymorphism.

This study aims to use machine learning model to predict laboratory aspirin resistance (AR) in Chinese stroke patients by incorporating patient charac...

OSAIRIS: Lessons Learned From the Hospital-Based Implementation and Evaluation of an Open-Source Deep-Learning Model for Radiotherapy Image Segmentation.

Several studies report the benefits and accuracy of using autosegmentation for organ at risk (OAR) outlining in radiotherapy treatment planning. Typic...

Boolean Computation in Single-Transistor Neuron.

Brain neurons exhibit far more sophisticated and powerful information-processing capabilities than the simple integrators commonly modeled in neuromor...

Non-specific myocardial fibrosis in young competitive athletes: clinical significance and risk prediction by a powerful machine learning-based model.

BACKGROUND: Non-specific myocardial fibrosis (NSMF) is a heterogeneous entity. We aimed to evaluate young athletes with and without NSMF to establish ...

Gene-diet interactions in carbonated sugar-sweetened beverage consumption and metabolic syndrome risk: A machine learning analysis in a large hospital-based cohort.

BACKGROUND AND AIM: Carbonated sugar-sweetened beverages (CSSB) intake has been increasingly linked to metabolic diseases. To investigate the associat...