Exercise & Fitness

Machine Learning for Predicting the 3-Year Risk of Incident Diabetes in Chinese Adults.

We aimed to establish and validate a risk assessment system that combines demographic and clinical variables to predict the 3-year risk of incident diabetes in Chinese adults. A 3-year cohort study was performed on 15,928 Chinese adults without diabetes at baseline. All participants were randomly divided into a training set ( = 7,940) and a validation set ( = 7,988). XGBoost method is an effecti...

A global neural network learning machine: Coupled integer and fractional calculus operator with an adaptive learning scheme.

Find the global optimal solution of the model is one promising research topic in computational intelligent community. Dependent on analogies to natural processes, the evolutionary swarm intelligent algorithms are widely used for solving global optimization problems which directed by the fitness values. In this paper, we propose one efficient fractional global learning machine (Fragmachine) which i...

Severe intraoperative bleeding predicts the risk of perioperative blood transfusion after robot-assisted radical prostatectomy.

To evaluate potential factors associated with the risk of perioperative blood transfusion (PBT) with implications on length of hospital stay (LOHS) an...

Optimizing Robotic Hysterectomy for the Patient Who Is Morbidly Obese with a Surgical Safety Pathway.

STUDY OBJECTIVE: Obesity is a growing worldwide epidemic, and patients classified as obese undergoing gynecologic robotic surgery are at increased ris...

Robot-assisted kidney transplantation is a safe alternative approach for morbidly obese patients with end-stage renal disease.

BACKGROUND: Many centres deny obese patients with a body mass index (BMI) >35 access to kidney transplantation due to increased intraoperative and pos...

Soft pneumatic elbow exoskeleton reduces the muscle activity, metabolic cost and fatigue during holding and carrying of loads.

To minimize fatigue, sustain workloads, and reduce the risk of injuries, the exoskeleton Carry was developed. Carry combines a soft human-machine inte...

Personalized machine learning of depressed mood using wearables.

Depression is a multifaceted illness with large interindividual variability in clinical response to treatment. In the era of digital medicine and prec...

SSMD: Semi-Supervised medical image detection with adaptive consistency and heterogeneous perturbation.

Semi-Supervised classification and segmentation methods have been widely investigated in medical image analysis. Both approaches can improve the perfo...

Search for H-Bonded Motifs in Liquid Ethylene Glycol Using a Machine Learning Strategy.

Trajectories of atomic positions derived from molecular dynamics (AIMD) simulations of H-bonded liquids contain a wealth of information on dominant s...

A Machine Learning Approach to the Interpretation of Cardiopulmonary Exercise Tests: Development and Validation.

OBJECTIVE: At present, there is no consensus on the best strategy for interpreting the cardiopulmonary exercise test's (CPET) results. This study is a...

Customizing Robot-Assisted Passive Neurorehabilitation Exercise Based on Teaching Training Mechanism.

Passive movement is an important mean of rehabilitation for stroke survivors in the early stage or with greater paralysis. The upper extremity robot i...

Validity of robotic simulation for high-stakes examination: a pilot study.

Simulation is increasingly being used to train surgeons and access technical competency in robotic skills. The construct validity of using simulation ...

Predictors of real-time fMRI neurofeedback performance and improvement - A machine learning mega-analysis.

Real-time fMRI neurofeedback is an increasingly popular neuroimaging technique that allows an individual to gain control over his/her own brain signal...

A real-time anatomy ıdentification via tool based on artificial ıntelligence for ultrasound-guided peripheral nerve block procedures: an accuracy study.

We aimed to assess the accuracy of an artificial intelligence (AI)-based real-time anatomy identification software specifically developed to ease imag...

Kernel machine SNP set analysis finds the association of BUD13, ZPR1, and APOA5 variants with metabolic syndrome in Tehran Cardio-metabolic Genetics Study.

Metabolic syndrome (MetS) is one of the most important risk factors for cardiovascular disease. The 11p23.3 chromosomal region plays a potential role ...

From Reflection to Action: Combining Machine Learning with Expert Knowledge for Nutrition Goal Recommendations.

Self-tracking can help personalize self-management interventions for chronic conditions like type 2 diabetes (T2D), but reflecting on personal data re...

The Application of an Adaptive Genetic Algorithm Based on Collision Detection in Path Planning of Mobile Robots.

An adaptive genetic algorithm based on collision detection (AGACD) is proposed to solve the problems of the basic genetic algorithm in the field of pa...

Automated accurate emotion recognition system using rhythm-specific deep convolutional neural network technique with multi-channel EEG signals.

Emotion is interpreted as a psycho-physiological process, and it is associated with personality, behavior, motivation, and character of a person. The ...

Machine-learning a virus assembly fitness landscape.

Realistic evolutionary fitness landscapes are notoriously difficult to construct. A recent cutting-edge model of virus assembly consists of a dodecahe...

Intrinsic motivation in virtual assistant interaction for fostering spontaneous interactions.

With the growing utility of today's conversational virtual assistants, the importance of user motivation in human-artificial intelligence interactions...