AIMC Topic: Young Adult
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Chest x-ray analysis with deep learning-based software as a triage test for pulmonary tuberculosis: a prospective study of diagnostic accuracy for culture-confirmed disease.
The Lancet. Digital health
Oct 19, 2020
BACKGROUND: Deep learning-based radiological image analysis could facilitate use of chest x-rays as triage tests for pulmonary tuberculosis in resource-limited settings. We sought to determine whether commercially available chest x-ray analysis softw...
Sex Factors
Adult
X-Rays
Deep Learning
Sensitivity and Specificity
HIV Infections
Male
Triage
Middle Aged
Image Processing, Computer-Assisted
Humans
Radiology
Lung
Body Mass Index
Software
Sputum
Age Factors
Prospective Studies
Pakistan
Female
Tuberculosis, Pulmonary
Young Adult
Mycobacterium tuberculosis
Effects of walking distance over robot-assisted training on walking ability in chronic stroke patients.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Oct 16, 2020
An understanding of the dose-response during training is important to identify the rehabilitation programs to obtain the improvement in chronic stroke patients. The purpose of this study was to determine whether distance-dose (distance walked across ...
A machine learning analysis of a "normal-like" IDH-WT diffuse glioma transcriptomic subgroup associated with prolonged survival reveals novel immune and neurotransmitter-related actionable targets.
BMC medicine
Oct 16, 2020
BACKGROUND: Classification of primary central nervous system tumors according to the World Health Organization guidelines follows the integration of histologic interpretation with molecular information and aims at providing the most precise prognosis...
Improving data acquisition speed and accuracy in sport using neural networks.
Journal of sports sciences
Oct 14, 2020
Video analysis is used in sport to derive kinematic variables of interest but often relies on time-consuming tracking operations. The purpose of this study was to determine speed, accuracy and reliability of 2D body landmark digitisation by a neural ...
Resting-state connectome-based support-vector-machine predictive modeling of internet gaming disorder.
Addiction biology
Oct 12, 2020
Internet gaming disorder (IGD), a worldwide mental health issue, has been widely studied using neuroimaging techniques during the last decade. Although dysfunctions in resting-state functional connectivity have been reported in IGD, mapping relations...
Natural Language Processing Reveals Vulnerable Mental Health Support Groups and Heightened Health Anxiety on Reddit During COVID-19: Observational Study.
Journal of medical Internet research
Oct 12, 2020
BACKGROUND: The COVID-19 pandemic is impacting mental health, but it is not clear how people with different types of mental health problems were differentially impacted as the initial wave of cases hit.
Young Adult
Adult
Mental Health
Male
Global Health
Middle Aged
Humans
Pandemics
COVID-19
Female
SARS-CoV-2
Natural Language Processing
Coronavirus Infections
Borderline Personality Disorder
Self-Help Groups
Anxiety
Betacoronavirus
Adolescent
Pneumonia, Viral
Suicidal Ideation
Stress Disorders, Post-Traumatic
Social Media
Machine learning from wristband sensor data for wearable, noninvasive seizure forecasting.
Epilepsia
Oct 11, 2020
OBJECTIVE: Seizure forecasting may provide patients with timely warnings to adapt their daily activities and help clinicians deliver more objective, personalized treatments. Although recent work has convincingly demonstrated that seizure risk assessm...
Development and evaluation of an artificial intelligence system for COVID-19 diagnosis.
Nature communications
Oct 9, 2020
Early detection of COVID-19 based on chest CT enables timely treatment of patients and helps control the spread of the disease. We proposed an artificial intelligence (AI) system for rapid COVID-19 detection and performed extensive statistical analys...
Noise reduction approach in pediatric abdominal CT combining deep learning and dual-energy technique.
European radiology
Oct 8, 2020
OBJECTIVES: To evaluate the image quality of low iodine concentration, dual-energy CT (DECT) combined with a deep learning-based noise reduction technique for pediatric abdominal CT, compared with standard iodine concentration single-energy polychrom...
MRI-based machine learning radiomics can predict HER2 expression level and pathologic response after neoadjuvant therapy in HER2 overexpressing breast cancer.
EBioMedicine
Oct 8, 2020
BACKGROUND: To use clinical and MRI radiomic features coupled with machine learning to assess HER2 expression level and predict pathologic response (pCR) in HER2 overexpressing breast cancer patients receiving neoadjuvant chemotherapy (NAC).
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