AIMC Topic: Age of Onset

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Development and validation of a new diabetes index for the risk classification of present and new-onset diabetes: multicohort study.

Scientific reports Aug 3, 2021
In this study, we aimed to propose a novel diabetes index for the risk classification based on machine learning techniques with a high accuracy for diabetes mellitus. Upon analyzing their demographic and biochemical data, we classified the 2013-16 Ko...
Humans Machine Learning Middle Aged Incidence ROC Curve Diabetes Mellitus Predictive Value of Tests Age of Onset Prospective Studies Republic of Korea Female Aged Male
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Data-driven approaches to advance research and clinical care for pediatric cancer.

Biochimica et biophysica acta. Reviews on cancer May 26, 2021
Pediatric cancer is a rare disease with a distinct etiology and mutational landscape compared with adult cancer. Multi-omics profiling of retrospective and prospective cohorts coupled with innovative computational analysis have been instrumental in u...
Biomarkers, Tumor Neoplasms Transcriptome Genomics Genetic Predisposition to Disease Humans Machine Learning Precision Medicine Medical Oncology Databases, Genetic Mutation Data Mining Age of Onset Pediatrics
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Development and Validation of a Machine Learning Model Using Administrative Health Data to Predict Onset of Type 2 Diabetes.

JAMA network open May 3, 2021
IMPORTANCE: Systems-level barriers to diabetes care could be improved with population health planning tools that accurately discriminate between high- and low-risk groups to guide investments and targeted interventions.
Diabetes Mellitus, Type 2 Age of Onset Retrospective Studies Decision Making, Computer-Assisted Electronic Health Records Adolescent Incidence Female Cohort Studies Aged Child Humans Aged, 80 and over Ontario Machine Learning Young Adult Algorithms Adult Forecasting Male Middle Aged Risk Assessment
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Identification of prognostic factors for pediatric myocarditis with a random forests algorithm-assisted approach.

Pediatric research Nov 18, 2020
BACKGROUND: Pediatric myocarditis is a rare disease with substantial mortality. Little is known regarding its prognostic factors. We hypothesize that certain comorbidities and procedural needs may increase risks of poor outcomes. This study aims to i...
Comorbidity Length of Stay Time Factors United States Myocarditis Databases, Factual Prognosis Risk Factors Risk Assessment Prevalence Data Mining Age of Onset Humans Machine Learning
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Psychosocial profiles and their predictors in epilepsy using patient-reported outcomes and machine learning.

Epilepsia May 20, 2020
OBJECTIVE: To apply unsupervised machine learning to patient-reported outcomes to identify clusters of epilepsy patients exhibiting unique psychosocial characteristics.
Unsupervised Machine Learning Middle Aged Psychology Humans Epilepsy Quality of Life Female Sex Factors Adult Age of Onset Cross-Sectional Studies Patient Reported Outcome Measures Male Socioeconomic Factors Age Factors Cluster Analysis
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Prediction of lithium response using clinical data.

Acta psychiatrica Scandinavica Nov 22, 2019
OBJECTIVE: Promptly establishing maintenance therapy could reduce morbidity and mortality in patients with bipolar disorder. Using a machine learning approach, we sought to evaluate whether lithium responsiveness (LR) is predictable using clinical ma...
Lithium Compounds Antimanic Agents ROC Curve Treatment Outcome Area Under Curve Age of Onset Sleep Initiation and Maintenance Disorders Clinical Decision Rules Adult Male Middle Aged Disease Progression Bipolar Disorder Humans Machine Learning Female Risk Factors
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Machine-learning-derived rules set excludes risk of Parkinson's disease in patients with olfactory or gustatory symptoms with high accuracy.

Journal of neurology Nov 1, 2019
BACKGROUND: Chemosensory loss is a symptom of Parkinson's disease starting already at preclinical stages. Their appearance without an identifiable etiology therefore indicates a possible early symptom of Parkinson's disease. Supervised machine-learni...
Young Adult Taste Disorders Adult Prospective Studies Male Female Middle Aged Reproducibility of Results Case-Control Studies Aged Humans Adolescent Aged, 80 and over Machine Learning Parkinson Disease Age of Onset Risk Olfaction Disorders
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Impact of age at onset on the phenomenology of depression in treatment-seeking adults in the STAR*D trial.

Journal of affective disorders Oct 26, 2019
BACKGROUND: - Adolescence is characterized by biological, emotional, and behavioral changes. The onset of depression during this vulnerable time may confer specific risks. This study examined whether symptoms of depression were associated with age at...
Female Young Adult Adult Male Middle Aged Severity of Illness Index Depression Adolescent Child Randomized Controlled Trials as Topic Regression Analysis Humans Age of Onset Neural Networks, Computer Patient Acceptance of Health Care Prospective Studies Retrospective Studies
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Prediction model development of late-onset preeclampsia using machine learning-based methods.

PloS one Aug 23, 2019
Preeclampsia is one of the leading causes of maternal and fetal morbidity and mortality. Due to the lack of effective preventive measures, its prediction is essential to its prompt management. This study aimed to develop models using machine learning...
Age of Onset Pregnancy Trimester, Second Gestational Age Pregnancy Trimester, Third Adult Logistic Models Support Vector Machine Bayes Theorem Humans Pre-Eclampsia Machine Learning Pregnancy Female
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Identifying Phenotypes of Atopic Dermatitis in a Longitudinal United States Cohort Using Unbiased Statistical Clustering.

The Journal of investigative dermatology Aug 22, 2019
Dermatitis, Atopic Humans United States Infant Longitudinal Studies Severity of Illness Index Machine Learning Cluster Analysis Diagnosis, Computer-Assisted Phenotype Registries Child, Preschool Female Age of Onset Child Infant, Newborn Male
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