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Deep Learning Algorithms to Predict Differential Renal Function <40% in Unilateral Hydronephrosis Based on Key Parameters of Urinary Tract Ultrasound.

Urology
OBJECTIVE: To identify the correlation between ultrasound findings and the incidence of differential renal function (DRF) <40%, we conducted an analysis of the key parameters of urinary tract ultrasound in children with unilateral hydronephrosis. For...

A computed tomography-based deep learning radiomics model for predicting the gender-age-physiology stage of patients with connective tissue disease-associated interstitial lung disease.

Computers in biology and medicine
OBJECTIVES: To explore the feasibility of using a diagnostic model constructed with deep learning-radiomics (DLR) features extracted from chest computed tomography (CT) images to predict the gender-age-physiology (GAP) stage of patients with connecti...

A novel deep neural network approach to detect and monitor cocaine drug abuse.

Computers in biology and medicine
PURPOSE: Cocaine is one of the most commonly used drugs that may lead to physical and mental health problems. It is necessary to identify individuals having cocaine use disorder as early as possible to monitor them properly. The objective of this wor...

Automatic implicit motive codings are at least as accurate as humans' and 99% faster.

Journal of personality and social psychology
Implicit motives, nonconscious needs that influence individuals' behaviors and shape their emotions, have been part of personality research for nearly a century but differ from personality traits. The implicit motive assessment is very resource-inten...

Automating the Addiction Behaviors Checklist for Problematic Opioid Use Identification.

JAMA psychiatry
IMPORTANCE: Individuals whose chronic pain is managed with opioids are at high risk of developing an opioid use disorder. Electronic health records (EHR) allow large-scale studies to identify a continuum of problematic opioid use, including opioid us...

Clinician Suicide Risk Assessment for Prediction of Suicide Attempt in a Large Health Care System.

JAMA psychiatry
IMPORTANCE: Clinical practice guidelines recommend suicide risk screening and assessment across behavioral health settings. The predictive accuracy of real-world clinician assessments for stratifying patients by risk of future suicidal behavior, howe...

Linking Symptom Inventories Using Semantic Textual Similarity.

Journal of neurotrauma
An extensive library of symptom inventories has been developed over time to measure clinical symptoms of traumatic brain injury (TBI), but this variety has led to several long-standing issues. Most notably, results drawn from different settings and s...

Comparison of deep learning models for facial attractiveness assessment on 3D photos.

Journal of dentistry
OBJECTIVES: Convolutional neural networks (CNNs) have demonstrated remarkable success in orthodontics. This study aimed to evaluate the accuracy and precision of several prominent CNN models for evaluating the facial attractiveness in Chinese orthodo...

Integrating large language models with human expertise for disease detection in electronic health records.

Computers in biology and medicine
OBJECTIVE: Electronic health records (EHR) are widely available to complement administrative data-based disease surveillance and healthcare performance evaluation. Defining conditions from EHR is labour-intensive and requires extensive manual labelli...

Explainable transformer-based deep survival analysis in childhood acute lymphoblastic leukemia.

Computers in biology and medicine
BACKGROUND: Acute lymphoblastic leukemia (ALL) is the most common type of leukemia among children and adolescents and can be life-threatening. The incidence of new cases has been increasing in recent years. Developing a predictive model to forecast t...