Primary Care

Exercise & Fitness

Latest AI and machine learning research in exercise & fitness for healthcare professionals.

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Factors Affecting Transperitoneal Robot-Assisted Laparoscopic Radical Prostatectomy.

To evaluate the impact of body mass index (BMI), preoperative risk classification, previous inguina...

Risk Assessment and Determination of Factors That Cause the Development of Hyperinsulinemia in School-Age Adolescents.

: Hyperinsulinemia and insulin resistance are not synonymous; if the risk of developing insulin resi...

End-to-End Autonomous Exploration with Deep Reinforcement Learning and Intrinsic Motivation.

Developing artificial intelligence (AI) agents is challenging for efficient exploration in visually ...

Advanced Compliant Anti-Gravity Robot System for Lumbar Stabilization Exercise Using Series Elastic Actuator.

: The lumbar stabilization exercise is one of the most recommended treatments in medical professiona...

Complex Deep Neural Networks from Large Scale Virtual IMU Data for Effective Human Activity Recognition Using Wearables.

Supervised training of human activity recognition (HAR) systems based on body-worn inertial measurem...

Feature Fusion of a Deep-Learning Algorithm into Wearable Sensor Devices for Human Activity Recognition.

This paper presents a wearable device, fitted on the waist of a participant that recognizes six acti...

Abnormal Activity Recognition from Surveillance Videos Using Convolutional Neural Network.

UNLABELLED: Background and motivation: Every year, millions of Muslims worldwide come to Mecca to pe...

A stratified analysis of a deep learning algorithm in the diagnosis of diabetic retinopathy in a real-world study.

BACKGROUND: The aim of our research was to prospectively explore the clinical value of a deep learni...

Cluster learning-assisted directed evolution.

Directed evolution, a strategy for protein engineering, optimizes protein properties (i.e., fitness)...

An interpretable machine learning model based on a quick pre-screening system enables accurate deterioration risk prediction for COVID-19.

A high-performing interpretable model is proposed to predict the risk of deterioration in coronaviru...

Combining machine learning and conventional statistical approaches for risk factor discovery in a large cohort study.

We present a simple and efficient hypothesis-free machine learning pipeline for risk factor discover...

Network analysis of trauma in patients with early-stage psychosis.

Childhood trauma (ChT) is a risk factor for psychosis. Negative lifestyle factors such as rumination...

Numerical Investigations through ANNs for Solving COVID-19 Model.

The current investigations of the COVID-19 spreading model are presented through the artificial neur...

Numerical investigations of the nonlinear smoke model using the Gudermannian neural networks.

These investigations are to find the numerical solutions of the nonlinear smoke model to exploit a s...

Detection of diabetes from whole-body MRI using deep learning.

Obesity is one of the main drivers of type 2 diabetes, but it is not uniformly associated with the d...

Multifactor Prediction of Embryo Transfer Outcomes Based on a Machine Learning Algorithm.

fertilization-embryo transfer (IVF-ET) technology make it possible for infertile couples to conceiv...

Neural interface systems with on-device computing: machine learning and neuromorphic architectures.

Development of neural interface and brain-machine interface (BMI) systems enables the treatment of n...

The Influence of Robot-Assisted Learning System on Health Literacy and Learning Perception.

Healthy aging is a new challenge for the world. Therefore, health literacy education is a key issue ...

Predicting Physical Exercise Adherence in Fitness Apps Using a Deep Learning Approach.

The use of mobile fitness apps has been on the rise for the last decade and especially during the wo...

Risk factor assessments of temporomandibular disorders via machine learning.

This study aimed to use artificial intelligence to determine whether biological and psychosocial fac...

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