AIMC Topic: Adult

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Performance of a Deep-Learning Neural Network Model in Assessing Skeletal Maturity on Pediatric Hand Radiographs.

Radiology
Purpose To compare the performance of a deep-learning bone age assessment model based on hand radiographs with that of expert radiologists and that of existing automated models. Materials and Methods The institutional review board approved the study....

Antioxidants from diet or supplements do not alter inflammatory markers in adults with cardiovascular disease risk. A pilot randomized controlled trial.

Nutrition research (New York, N.Y.)
Antioxidants have been reported to have anti-inflammatory effects, but there is a lack of research comparing food to supplement antioxidant sources. The aim of this study was to determine if increases in intake of foods naturally rich in antioxidants...

Personality biomarkers of pathological gambling: A machine learning study.

Journal of neuroscience methods
BACKGROUND: The application of artificial intelligence to extract predictors of Gambling disorder (GD) is a new field of study. A plethora of studies have suggested that maladaptive personality dispositions may serve as risk factors for GD.

Robotic-assisted single-port donor nephrectomy using the da Vinci single-site platform.

The Journal of surgical research
BACKGROUND: Although single-port donor nephrectomy offers improved cosmetic outcomes, technical challenges have limited its application to selected centers. Our center has performed over 400 single-port donor nephrectomies. The da Vinci single-site r...

Quantitative surface analysis of combined MRI and PET enhances detection of focal cortical dysplasias.

NeuroImage
OBJECTIVE: Focal cortical dysplasias (FCDs) often cause pharmacoresistant epilepsy, and surgical resection can lead to seizure-freedom. Magnetic resonance imaging (MRI) and positron emission tomography (PET) play complementary roles in FCD identifica...

Supervised learning techniques and their ability to classify a change of direction task strategy using kinematic and kinetic features.

Journal of biomechanics
This study examines the ability of commonly used supervised learning techniques to classify the execution of a maximum effort change of direction task into predefined movement pattern as well as the influence of fuzzy executions and the impact of sel...

Inclusion of service robots in the daily lives of frail older users: A step-by-step definition procedure on users' requirements.

Archives of gerontology and geriatrics
The implications for the inclusion of robots in the daily lives of frail older adults, especially in relation to these population needs, have not been extensively studied. The "Multi-Role Shadow Robotic System for Independent Living" (SRS) project ha...

Evaluation of genotoxic effects in Brazilian agricultural workers exposed to pesticides and cigarette smoke using machine-learning algorithms.

Environmental science and pollution research international
Monitoring exposure to xenobiotics by biomarker analyses, such as a micronucleus assay, is extremely important for the precocious detection and prevention of diseases, such as oral cancer. The aim of this study was to evaluate genotoxic effects in ru...

MRI features predict p53 status in lower-grade gliomas via a machine-learning approach.

NeuroImage. Clinical
BACKGROUND: P53 mutation status is a pivotal biomarker for gliomas. Here, we developed a machine-learning model to predict p53 status in lower-grade gliomas based on radiomic features extracted from conventional magnetic resonance (MR) images.