AIMC Topic: Young Adult

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Machine Learning Identifies Large-Scale Reward-Related Activity Modulated by Dopaminergic Enhancement in Major Depression.

Biological psychiatry. Cognitive neuroscience and neuroimaging Oct 22, 2019
BACKGROUND: Theoretical models have emphasized systems-level abnormalities in major depressive disorder (MDD). For unbiased yet rigorous evaluations of pathophysiological mechanisms underlying MDD, it is critically important to develop data-driven ap...
Reward Dopamine Antidepressive Agents, Second-Generation Young Adult Amisulpride Adult Humans Male Machine Learning Depressive Disorder, Major Female Depression Double-Blind Method
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Machine learning for prediction of septic shock at initial triage in emergency department.

Journal of critical care Oct 22, 2019
BACKGROUND: We hypothesized utilizing machine learning (ML) algorithms for screening septic shock in ED would provide better accuracy than qSOFA or MEWS.
Republic of Korea Female Aged Young Adult Adult Machine Learning Male Software Middle Aged Triage Algorithms Sepsis Area Under Curve Humans Prognosis Hospital Mortality Emergency Service, Hospital Electronic Health Records Multivariate Analysis Vital Signs Shock, Septic Support Vector Machine
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Analysis of substance use and its outcomes by machine learning I. Childhood evaluation of liability to substance use disorder.

Drug and alcohol dependence Oct 22, 2019
BACKGROUND: Substance use disorder (SUD) exacts enormous societal costs in the United States, and it is important to detect high-risk youths for prevention. Machine learning (ML) is the method to find patterns and make prediction from data. We hypoth...
Child ROC Curve Longitudinal Studies Predictive Value of Tests Substance-Related Disorders Young Adult Outcome Assessment, Health Care Adult Humans Psychological Techniques Male Machine Learning Severity of Illness Index Female Adolescent Reproducibility of Results
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Improving automatic delineation for head and neck organs at risk by Deep Learning Contouring.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Oct 22, 2019
INTRODUCTION: Adequate head and neck (HN) organ-at-risk (OAR) delineation is crucial for HN radiotherapy and for investigating the relationships between radiation dose to OARs and radiation-induced side effects. The automatic contouring algorithms th...
Observer Variation Young Adult Adult Male Middle Aged Humans Deep Learning Neural Networks, Computer Adolescent Algorithms Head and Neck Neoplasms Female Neck Aged Neoplasm Staging Organs at Risk Radiotherapy Planning, Computer-Assisted
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SVM recursive feature elimination analyses of structural brain MRI predicts near-term relapses in patients with clinically isolated syndromes suggestive of multiple sclerosis.

NeuroImage. Clinical Oct 22, 2019
Machine learning classification is an attractive approach to automatically differentiate patients from healthy subjects, and to predict future disease outcomes. A clinically isolated syndrome (CIS) is often the first presentation of multiple sclerosi...
Support Vector Machine Follow-Up Studies Magnetic Resonance Imaging Male Multiple Sclerosis Gray Matter Humans Neuroimaging Middle Aged White Matter Retrospective Studies Disease Progression Female Adolescent Young Adult Image Processing, Computer-Assisted Adult
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Deep Learning Based on Standard H&E Images of Primary Melanoma Tumors Identifies Patients at Risk for Visceral Recurrence and Death.

Clinical cancer research : an official journal of the American Association for Cancer Research Oct 21, 2019
PURPOSE: Biomarkers for disease-specific survival (DSS) in early-stage melanoma are needed to select patients for adjuvant immunotherapy and accelerate clinical trial design. We present a pathology-based computational method using a deep neural netwo...
Follow-Up Studies Area Under Curve Biopsy Neoplasm Recurrence, Local Middle Aged Disease Progression Deep Learning Image Processing, Computer-Assisted Staining and Labeling Algorithms Aged Retrospective Studies Aged, 80 and over Female Young Adult Humans Melanoma Adult Neural Networks, Computer Survival Rate Risk Factors Male
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Applying Machine Learning Techniques in Nomogram Prediction and Analysis for SMILE Treatment.

American journal of ophthalmology Oct 21, 2019
PURPOSE: To analyze the outcome of machine learning technique for prediction of small incision lenticule extraction (SMILE) nomogram.
Myopia Nomograms Lasers, Excimer Astigmatism Corneal Stroma Corneal Surgery, Laser Young Adult Adult Male Humans Middle Aged Machine Learning Refraction, Ocular Prospective Studies Female
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The FluPRINT dataset, a multidimensional analysis of the influenza vaccine imprint on the immune system.

Scientific data Oct 21, 2019
Machine learning has the potential to identify novel biological factors underlying successful antibody responses to influenza vaccines. The first attempts have revealed a high level of complexity in establishing influenza immunity, and many different...
Humans Young Adult Adult Male Middle Aged Infant Adolescent Machine Learning Cytokines Female Aged Aged, 80 and over Immune System Antibody Formation Hemagglutination Inhibition Tests Child, Preschool Child Immunophenotyping Influenza Vaccines Immunogenicity, Vaccine
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An Exploration of Machine Learning Methods for Robust Boredom Classification Using EEG and GSR Data.

Sensors (Basel, Switzerland) Oct 20, 2019
In recent years, affective computing has been actively researched to provide a higher level of emotion-awareness. Numerous studies have been conducted to detect the user's emotions from physiological data. Among a myriad of target emotions, boredom, ...
Humans Machine Learning ROC Curve Area Under Curve Discriminant Analysis Electroencephalography Galvanic Skin Response Boredom Female Young Adult Adult Male Surveys and Questionnaires
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The diagnosticity of psychophysiological signatures: Can we disentangle mental workload from acute stress with ECG and fNIRS?

International journal of psychophysiology : official journal of the International Organization of Psychophysiology Oct 19, 2019
The ability to identify reliable and sensitive physiological signatures of psychological dimensions is key to developing intelligent adaptive systems that may in turn help to mitigate human error in complex operations. The challenge of this endeavor ...
Electrocardiography Memory, Short-Term Psychomotor Performance Executive Function Male Anxiety Spectroscopy, Near-Infrared Prefrontal Cortex Stress, Psychological Humans Machine Learning Female Young Adult Adult
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