AIMC Topic: Adolescent

Clear Filters Showing 1901 to 1910 of 3540 articles

A novel image signature-based radiomics method to achieve precise diagnosis and prognostic stratification of gliomas.

Laboratory investigation; a journal of technical methods and pathology
Radiomics has potential advantages in the noninvasive histopathological and molecular diagnosis of gliomas. We aimed to develop a novel image signature (IS)-based radiomics model to achieve multilayered preoperative diagnosis and prognostic stratific...

Machine learning-based automated classification of headache disorders using patient-reported questionnaires.

Scientific reports
Classification of headache disorders is dependent on a subjective self-report from patients and its interpretation by physicians. We aimed to apply objective data-driven machine learning approaches to analyze patient-reported symptoms and test the fe...

A comparison of regularized logistic regression and random forest machine learning models for daytime diagnosis of obstructive sleep apnea.

Medical & biological engineering & computing
A major challenge in big and high-dimensional data analysis is related to the classification and prediction of the variables of interest by characterizing the relationships between the characteristic factors and predictors. This study aims to assess ...

Machine Learning Models to Predict Childhood and Adolescent Obesity: A Review.

Nutrients
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 current and near-future health systems, given the association of these conditions with different co...

Predicting In-Hospital Mortality at Admission to the Medical Ward: A Big-Data Machine Learning Model.

The American journal of medicine
BACKGROUND: General medical wards admit high-risk patients. Artificial intelligence algorithms can use big data for developing models to assess patients' risk stratification. The aim of this study was to develop a mortality prediction machine learnin...

Reconfiguration of αmplitude driven dominant coupling modes (DoCM) mediated by α-band in adolescents with schizophrenia spectrum disorders.

Progress in neuro-psychopharmacology & biological psychiatry
Electroencephalography (EEG) based biomarkers have been shown to correlate with the presence of psychotic disorders. Increased delta and decreased alpha power in psychosis indicate an abnormal arousal state. We investigated brain activity across the ...

Deep Learning for Pediatric Posterior Fossa Tumor Detection and Classification: A Multi-Institutional Study.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Posterior fossa tumors are the most common pediatric brain tumors. MR imaging is key to tumor detection, diagnosis, and therapy guidance. We sought to develop an MR imaging-based deep learning model for posterior fossa tumor d...

Classification of cervical neoplasms on colposcopic photography using deep learning.

Scientific reports
Colposcopy is widely used to detect cervical cancers, but experienced physicians who are needed for an accurate diagnosis are lacking in developing countries. Artificial intelligence (AI) has been recently used in computer-aided diagnosis showing rem...

Rapid identification of COVID-19 severity in CT scans through classification of deep features.

Biomedical engineering online
BACKGROUND: Chest CT is used for the assessment of the severity of patients infected with novel coronavirus 2019 (COVID-19). We collected chest CT scans of 202 patients diagnosed with the COVID-19, and try to develop a rapid, accurate and automatic t...