Obesity

Validation of a Novel Perceptual Body Image Assessment Method Using Mobile Digital Imaging Analysis: A Cross-Sectional Multicenter Evaluation in a Multiethnic Sample.

Given that mobile digital imaging analyses (DIA) are equipped to automate body composition and subsequently alter one's appearance at a given objective body fat percent (BF%), the purpose of this study was to validate the use of this tool for assessments of body image. Participants (f = 134, m = 89) from two separate centers underwent body composition scans using a mobile DIA and completed the Mul...

CIRCE: Web-Based Platform for the Prediction of Cannabinoid Receptor Ligands Using Explainable Machine Learning.

The endocannabinoid system, which includes cannabinoid receptor 1 and 2 subtypes (CBR and CBR, respectively), is responsible for the onset of various pathologies including neurodegeneration, cancer, neuropathic and inflammatory pain, obesity, and inflammatory bowel disease. Given the high similarity of CBR and CBR, generating subtype-selective ligands is still an open challenge. In this work, the ...

The Nutritional Content of Meal Images in Free-Living Conditions-Automatic Assessment with goFOOD.

A healthy diet can help to prevent or manage many important conditions and diseases, particularly obesity, malnutrition, and diabetes. Recent advancem...

Deep learning reconstruction vs standard reconstruction for abdominal CT: the influence of BMI.

OBJECTIVE: This study aimed to evaluate the image quality and lesion conspicuity of the deep learning image reconstruction (DLIR) algorithm compared w...

Bilateral subgaleal hematoma after a robot-assisted radical prostatectomy: an uncommon complication.

Robot-assisted radical prostatectomy is a relatively recent technique. Its advantages include less invasiveness and better pain management, but has sp...

Early Prediction of Progression to Alzheimer's Disease using Multi-Modality Neuroimages by a Novel Ordinal Learning Model ADPacer.

Machine learning has shown great promise for integrating multi-modality neuroimaging datasets to predict the risk of progression/conversion to Alzheim...

Early prediction of body composition parameters on metabolically unhealthy in the Chinese population via advanced machine learning.

BACKGROUND: Metabolic syndrome (Mets) is considered a global epidemic of the 21st century, predisposing to cardiometabolic diseases. This study aims t...

Multimodal deep learning as a next challenge in nutrition research: tailoring fermented dairy products based on -mediated lipid metabolism.

Deep learning is evolving in nutritional epidemiology to address challenges including precise nutrition and data-driven disease modeling. Fermented da...

A comparison of perioperative outcomes of transperitoneal versus retroperitoneal robot-assisted partial nephrectomy: a systematic review.

RAPN can be carried out via a transperitoneal or retroperitoneal approach. The choice between the two approaches is open to debate and usually based o...

Artificial Intelligence (AI) in pediatric endocrinology.

Artificial Intelligence (AI) is integrating itself throughout the medical community. AI's ability to analyze complex patterns and interpret large amou...

A Comparative Analysis of Various Machine Learning Algorithms to Improve the Accuracy of HbA1c Estimation Using Wrist PPG Data.

Due to the inconvenience of drawing blood and the possibility of infection associated with invasive methods, research on non-invasive glycated hemoglo...

Automated Deep Learning-Based Segmentation of Abdominal Adipose Tissue on Dixon MRI in Adolescents: A Prospective Population-Based Study.

The prevalence of childhood obesity has increased significantly worldwide, highlighting a need for accurate noninvasive quantification of body fat di...

Adolescent relational behaviour and the obesity pandemic: A descriptive study applying social network analysis and machine learning techniques.

AIM: To study the existence of subgroups by exploring the similarities between the attributes of the nodes of the groups, in relation to diet and gend...

-derived postbiotics inhibited digestion of triglycerides, glycerol phospholipids and sterol lipids allosteric regulation of BSSL, PTL and PLA2 to prevent obesity: perspectives on deep learning integrated multi-omics.

The anti-obesity potential of probiotics has been widely reported, however their utilization in high-risk patients and potential adverse reactions hav...

Deep learning for obstructive sleep apnea diagnosis based on single channel oximetry.

Obstructive sleep apnea (OSA) is a serious medical condition with a high prevalence, although diagnosis remains a challenge. Existing home sleep tests...

Effect of Lower Limb Exoskeleton on the Modulation of Neural Activity and Gait Classification.

Neurorehabilitation with robotic devices requires a paradigm shift to enhance human-robot interaction. The coupling of robot assisted gait training (R...

Molecular bases of comorbidities: present and future perspectives.

Co-occurrence of diseases decreases patient quality of life, complicates treatment choices, and increases mortality. Analyses of electronic health rec...

Explainable artificial intelligence on life satisfaction, diabetes mellitus and its comorbid condition.

This study uses artificial intelligence for testing (1) whether the comorbidity of diabetes and its comorbid condition is very strong in the middle-ag...

Stratification of diabetes in the context of comorbidities, using representation learning and topological data analysis.

Diabetes is a heterogenous, multimorbid disorder with a large variation in manifestations, trajectories, and outcomes. The aim of this study is to val...

Non-traditional data sources in obesity research: a systematic review of their use in the study of obesogenic environments.

BACKGROUND: The complex nature of obesity increasingly requires a comprehensive approach that includes the role of environmental factors. For understa...