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Age Factors

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Logistic regression and machine learning predicted patient mortality from large sets of diagnosis codes comparably.

Journal of clinical epidemiology
OBJECTIVE: The objective of the study was to compare the performance of logistic regression and boosted trees for predicting patient mortality from large sets of diagnosis codes in electronic healthcare records.

Dynamics of Systemic Inflammation as a Function of Developmental Stage in Pediatric Acute Liver Failure.

Frontiers in immunology
The Pediatric Acute Liver Failure (PALF) study is a multicenter, observational cohort study of infants and children diagnosed with this complex clinical syndrome. Outcomes in PALF reflect interactions among the child's clinical condition, response to...

Age-group determination of living individuals using first molar images based on artificial intelligence.

Scientific reports
Dental age estimation of living individuals is difficult and challenging, and there is no consensus method in adults with permanent dentition. Thus, we aimed to provide an accurate and robust artificial intelligence (AI)-based diagnostic system for a...

Prevalence of and Risk Factors for Hypovitaminosis D in Patients with Rotator Cuff Tears.

Clinics in orthopedic surgery
BACKGROUD: It has been reported that vitamin D may play an important role in rotator cuff tears. However, there has been limited information about the prevalence of and risk factors for hypovitaminosis D in patients with rotator cuff tears. Therefore...

PsychoAge and SubjAge: development of deep markers of psychological and subjective age using artificial intelligence.

Aging
Aging clocks that accurately predict human age based on various biodata types are among the most important recent advances in biogerontology. Since 2016 multiple deep learning solutions have been created to interpret facial photos, omics data, and cl...

Fully‑automated deep‑learning segmentation of pediatric cardiovascular magnetic resonance of patients with complex congenital heart diseases.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: For the growing patient population with congenital heart disease (CHD), improving clinical workflow, accuracy of diagnosis, and efficiency of analyses are considered unmet clinical needs. Cardiovascular magnetic resonance (CMR) imaging of...

Training confounder-free deep learning models for medical applications.

Nature communications
The presence of confounding effects (or biases) is one of the most critical challenges in using deep learning to advance discovery in medical imaging studies. Confounders affect the relationship between input data (e.g., brain MRIs) and output variab...

Using machine learning-based analytics of daily activities to identify modifiable risk factors for falling in Parkinson's disease.

Parkinsonism & related disorders
BACKGROUND: Although risk factors that lead to falling in Parkinson's disease (PD) have been previously studied, the established predictors are mostly non-modifiable. A novel method for fall risk assessment may provide more insight into preventable h...

Type IV Collagen 7S Is the Most Accurate Test For Identifying Advanced Fibrosis in NAFLD With Type 2 Diabetes.

Hepatology communications
This study aimed to examine whether the diagnostic accuracy of four noninvasive tests (NITs) for detecting advanced fibrosis in nonalcoholic fatty liver disease (NAFLD) is maintained or is inferior to with or without the presence of type 2 diabetes. ...