Primary Care

Exercise & Fitness

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

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Geographically weighted machine learning model for untangling spatial heterogeneity of type 2 diabetes mellitus (T2D) prevalence in the USA.

Type 2 diabetes mellitus (T2D) prevalence in the United States varies substantially across spatial a...

A first perturbome of Pseudomonas aeruginosa: Identification of core genes related to multiple perturbations by a machine learning approach.

Tolerance to stress conditions is vital for organismal survival, including bacteria under specific e...

Machine learning applied for metabolic flux-based control of micro-aerated fermentations in bioreactors.

Various bio-based processes depend on controlled micro-aerobic conditions to achieve a satisfactory ...

The effect of diabetes on major robotic hepatectomy.

Studies regarding the influence of diabetes on perioperative outcomes after major hepatectomy are co...

Classification of red blood cell aggregation using empirical wavelet transform analysis of ultrasonic radiofrequency echo signals.

Grading red blood cell (RBC) aggregation is important for the early diagnosis and prevention of rela...

Application Prospect of Artificial Intelligence in Rehabilitation and Management of Myasthenia Gravis.

Myasthenia gravis (MG) is a chronic autoimmune disease of the nervous system, which is still incurab...

Prediction of newborn's body mass index using nationwide multicenter ultrasound data: a machine-learning study.

BACKGROUND: This study introduced machine learning approaches to predict newborn's body mass index (...

The potential of artificial intelligence in enhancing adult weight loss: a scoping review.

OBJECTIVE: To present an overview of how artificial intelligence (AI) could be used to regulate eati...

In silico design of novel aptamers utilizing a hybrid method of machine learning and genetic algorithm.

Aptamers can be regarded as efficient substitutes for monoclonal antibodies in many diagnostic and t...

On the Impact of Biceps Muscle Fatigue in Human Activity Recognition.

Nowadays, Human Activity Recognition (HAR) systems, which use wearables and smart systems, are a par...

Assessing Dry Weight of Hemodialysis Patients via Sparse Laplacian Regularized RVFL Neural Network with L-Norm.

Dry weight is the normal weight of hemodialysis patients after hemodialysis. If the amount of water ...

Risk factors analysis of COVID-19 patients with ARDS and prediction based on machine learning.

COVID-19 is a newly emerging infectious disease, which is generally susceptible to human beings and ...

Oxynet: A collective intelligence that detects ventilatory thresholds in cardiopulmonary exercise tests.

The problem of the automatic determination of the first and second ventilatory thresholds (VT1 and V...

The Metabolic Cost of Exercising With a Robotic Exoskeleton: A Comparison of Healthy and Neurologically Impaired People.

While neuro-recovery is maximized through active engagement, it has been suggested that the use of r...

AI Therapist Realizing Expert Verbal Cues for Effective Robot-Assisted Gait Training.

Repetitive and specific verbal cues by a therapist are essential in aiding a patient's motivation an...

Deep CHORES: Estimating Hallmark Measures of Physical Activity Using Deep Learning.

Wrist accelerometers for assessing hallmark measures of physical activity (PA) are rapidly growing w...

Ranking of a wide multidomain set of predictor variables of children obesity by machine learning variable importance techniques.

The increased prevalence of childhood obesity is expected to translate in the near future into a con...

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