Latest AI and machine learning research in obesity for healthcare professionals.
AIM: The surgical treatment of endometrial cancer (EC) can be more complicated in obese patients. Robotic surgery could simplify the surgical approach in these patients. The aim of our study was to compare the outcomes of robotic surgery in obese (body mass index ≥30 kg/m ) and nonobese patients.
To evaluate the feasibility and outcomes of performing robot-assisted pelvic surgery at a reduced angle of Trendelenburg position. This was a prospective case-control study of 67 patients in 2:1 ratio. Controls were operated with steep Trendelenburg position of 30°, whereas cases were operated using a graduated method to achieve minimal optimal angle of operating table. Various body habitus parame...
The prevalence of childhood and adolescence overweight an obesity is raising at an alarming rate in many countries. This poses a serious threat to the...
BACKGROUND: Rehabilitation robots integrated with brain-machine interaction (BMI) can facilitate stroke patients' recovery by closing the loop between...
We sought to identify the factors associated with deterioration of renal functions after robot-assisted radical cystectomy, and to develop a nomogram...
Genetic studies have recently highlighted the importance of fat distribution, as well as overall adiposity, in the pathogenesis of obesity-associated ...
Large-scale, sometimes nationwide, prospective genomic cohorts biobanking rich biological specimens such as blood, urine and tissues, have been establ...
This study aimed to identify clinical features for prognosing mortality risk using machine-learning methods in patients with coronavirus disease 2019 ...
We sought to compare the outcomes of patients who underwent an open robotic ureteroneocystostomy for ureteral obstruction. Retrospective review was...
Human operator control of brain-actuated robot steering based on electroencephalograph (EEG)-signals is a complex behavior consisting of surroundings ...
The use of artificial intelligence in numerous prediction and classification tasks, including clinical research and healthcare management, is becoming...
Diabetes is a chronic disease that occurs when the pancreas does not generate sufficient insulin or the body cannot effectively utilize the produced i...
BACKGROUND: The early life risk factors of childhood obesity among preterm infants are unclear and little is known about the influence of the feeding ...
Arbutus unedo L. (strawberry tree) has showed considerable content in phenolic compounds, especially flavan-3-ols (catechin, gallocatechin, among othe...
This paper focus on a neural network classification model to estimate the association among gender, race, BMI, age, smoking, kidney disease and diabet...
OBJECTIVE: To determine how body mass index (BMI) affects the follicular fluid cytokine milieu and investigate how this inflammatory environment impac...
Research on heart rate (HR) estimation using wrist-worn photoplethysmography (PPG) sensors have progressed rapidly owing to the prominence of commerci...
To identify the most important factors that impact brain volume, while accounting for potential collinearity, we used a data-driven machine-learning a...
The factors that determine Serum Thyrotropin (TSH) levels have been examined through different methods, using different covariates. However, the use o...
The importance of eating behavior risk factors in the primary prevention of obesity has been established. Researchers mostly use the linear model to d...