AIMC Topic: Young Adult
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Deep learning for efficient reconstruction of highly accelerated 3D FLAIR MRI in neurological deficits.
Magma (New York, N.Y.)
Aug 30, 2024
OBJECTIVE: To compare compressed sensing (CS) and the Cascades of Independently Recurrent Inference Machines (CIRIM) with respect to image quality and reconstruction times when 12-fold accelerated scans of patients with neurological deficits are reco...
Artifacts
Signal-To-Noise Ratio
Nervous System Diseases
White Matter
Child
Imaging, Three-Dimensional
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Image Interpretation, Computer-Assisted
Middle Aged
Deep Learning
Adolescent
Child, Preschool
Humans
Algorithms
Brain
Female
Reproducibility of Results
Aged
Young Adult
Adult
Male
Forecasting the incidence frequencies of schizophrenia using deep learning.
Asian journal of psychiatry
Aug 30, 2024
Mental disorders are becoming increasingly prevalent worldwide, and accurate incidence forecasting is crucial for effective mental health strategies. This study developed a long short-term memory (LSTM)-based recurrent neural network model to predict...
Salivary Molecular Spectroscopy with Machine Learning Algorithms for a Diagnostic Triage for Amelogenesis Imperfecta.
International journal of molecular sciences
Aug 30, 2024
Amelogenesis imperfecta (AI) is a genetic disease characterized by poor formation of tooth enamel. AI occurs due to mutations, especially in AMEL, ENAM, KLK4, MMP20, and FAM83H, associated with changes in matrix proteins, matrix proteases, cell-matri...
Sex determination through maxillary dental arch and skeletal base measurements using machine learning.
Head & face medicine
Aug 30, 2024
BACKGROUND: Cranial, facial, nasal, and maxillary widths have been shown to be significantly affected by the individual's sex. The present study aims to use measurements of dental arch and maxillary skeletal base to determine sex, employing supervise...
Identifying Elective Induction of Labor among a Diverse Pregnant Population from Electronic Health Records within a Large Integrated Health Care System.
American journal of perinatology
Aug 29, 2024
OBJECTIVE:  Distinguishing between medically indicated induction of labor (iIOL) and elective induction of labor (eIOL) is a daunting process for researchers. We aimed to develop a Natural Language Processing (NLP) algorithm to identify eIOLs from el...
Machine Learning Model Reveals Determinators for Admission to Acute Mental Health Wards From Emergency Department Presentations.
International journal of mental health nursing
Aug 29, 2024
This research addresses the critical issue of identifying factors contributing to admissions to acute mental health (MH) wards for individuals presenting to the emergency department (ED) with MH concerns as their primary issue, notably suicidality. T...
Artificial neural network inference analysis identified novel genes and gene interactions associated with skeletal muscle aging.
Journal of cachexia, sarcopenia and muscle
Aug 29, 2024
BACKGROUND: Sarcopenia is an age-related muscle disease that increases the risk of falls, disabilities, and death. It is associated with increased muscle protein degradation driven by molecular signalling pathways including Akt and FOXO1. This study ...
Prediction model for lateral lymph node metastasis of papillary thyroid carcinoma in children and adolescents based on ultrasound imaging and clinical features: a retrospective study.
BMC medical imaging
Aug 29, 2024
BACKGROUND: The presence of lateral lymph node metastases (LNM) in paediatric patients with papillary thyroid cancer (PTC) is an independent risk factor for recurrence. We aimed to identify risk factors and establish a prediction model for lateral LN...
Young Adult
Male
Risk Assessment
Adolescent
Thyroid Neoplasms
Humans
Retrospective Studies
Female
Risk Factors
Predictive Learning Models
Regression Analysis
Predictive Value of Tests
Area Under Curve
Reference Values
Thyroid Cancer, Papillary
Ultrasonography
ROC Curve
Lymph Nodes
Lymphatic Metastasis
Leveraging artificial intelligence to identify the psychological factors associated with conspiracy theory beliefs online.
Nature communications
Aug 29, 2024
Given the profound societal impact of conspiracy theories, probing the psychological factors associated with their spread is paramount. Most research lacks large-scale behavioral outcomes, leaving factors related to actual online support for conspira...
Consumer-priced wearable sensors combined with deep learning can be used to accurately predict ground reaction forces during various treadmill running conditions.
PeerJ
Aug 29, 2024
Ground reaction force (GRF) data is often collected for the biomechanical analysis of running, due to the performance and injury risk insights that GRF analysis can provide. Traditional methods typically limit GRF collection to controlled lab environ...
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