Exercise & Fitness

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 learning algorithm (DLA) to detect referable diabetic retinopathy (DR) in different subgroups stratified by types of diabetes, blood pressure, sex, BMI, age, glycosylated hemoglobin (HbA1c), diabetes duration, urine albumin-to-creatinine ratio (UACR), and estimated glomerular filtration rate (eGFR) at a r...

Cluster learning-assisted directed evolution.

Directed evolution, a strategy for protein engineering, optimizes protein properties (i.e., fitness) by expensive and time-consuming screening or selection of large mutational sequence space. Machine learning-assisted directed evolution (MLDE), which screens sequence properties , can accelerate the optimization and reduce the experimental burden. This work introduces a MLDE framework, cluster lear...

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 coronavirus disease 2019 (COVID-19) patients. The model was ...

Does prior transurethral resection of prostate affect the functional and oncological outcomes of robot-assisted radical prostatectomy? A matched-pair analysis.

Robot-assisted radical prostatectomy (RARP) is challenging in men with prior history of transurethral resection of the prostate (TURP). Few studies an...

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 discovery that accounts for non-linearity and interaction ...

The Internet of Cooperative Agents Architecture (X-IoCA) for Robots, Hybrid Sensor Networks, and MEC Centers in Complex Environments: A Search and Rescue Case Study.

Cloud robotics and advanced communications can foster a step-change in cooperative robots and hybrid wireless sensor networks (H-WSN) for demanding en...

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, negative schemas, and poor diet and exercise are...

Numerical Investigations through ANNs for Solving COVID-19 Model.

The current investigations of the COVID-19 spreading model are presented through the artificial neuron networks (ANNs) with training of the Levenberg-...

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 stochastic framework called gudermannian neural wor...

A new ML-based approach to enhance student engagement in online environment.

The educational research is increasingly emphasizing the potential of student engagement and its impact on performance, retention and persistence. Thi...

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 disease. The location of fat accumulation is critic...

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 conceive a baby successfully. Nevertheless, IVF-ET does n...

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 neurological disorders including cognitive, sensory...

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 in the current health care field. This research ha...

Job characteristics of a Malaysian bank's anti-money laundering system and its employees' job satisfaction.

Banks and financial institutions are vulnerable to money laundering (ML) as a result of crime proceeds infiltrating banks in the form of significant ...

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 worldwide SARS-CoV-2 pandemic, which led to the clos...

Machine learning-guided acyl-ACP reductase engineering for improved in vivo fatty alcohol production.

Alcohol-forming fatty acyl reductases (FARs) catalyze the reduction of thioesters to alcohols and are key enzymes for microbial production of fatty al...

Risk factor assessments of temporomandibular disorders via machine learning.

This study aimed to use artificial intelligence to determine whether biological and psychosocial factors, such as stress, socioeconomic status, and wo...

Explainable machine learning models of major crop traits from satellite-monitored continent-wide field trial data.

Four species of grass generate half of all human-consumed calories. However, abundant biological data on species that produce our food remain largely ...

Artificial neural network and decision tree models of post-stroke depression at 3 months after stroke in patients with BMI ≥ 24.

OBJECTIVE: Previous studies have shown that excess weight (including obesity and overweight) can increase the risk of cardiovascular, cerebrovascular ...