AIMC Topic: Age Factors

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Assessment of Facial Morphologic Features in Patients With Congenital Adrenal Hyperplasia Using Deep Learning.

JAMA network open Nov 2, 2020
IMPORTANCE: Congenital adrenal hyperplasia (CAH) is the most common primary adrenal insufficiency in children, involving excess androgens secondary to disrupted steroidogenesis as early as the seventh gestational week of life. Although structural bra...
Humans Female Young Adult Adult Cross-Sectional Studies Image Processing, Computer-Assisted Longitudinal Studies Age Factors Face California Adrenal Hyperplasia, Congenital Male Deep Learning Adolescent Child, Preschool Child
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Predicting preventable hospital readmissions with causal machine learning.

Health services research Oct 30, 2020
OBJECTIVE: To assess both the feasibility and potential impact of predicting preventable hospital readmissions using causal machine learning applied to data from the implementation of a readmissions prevention intervention (the Transitions Program).
Diagnostic Techniques and Procedures Continuity of Patient Care Health Status Age Factors Sex Factors Patient Readmission Health Services Research Aged Humans Male Machine Learning Middle Aged Retrospective Studies Risk Assessment Electronic Health Records Severity of Illness Index Female Risk Factors
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Discrimination of alcohol dependence based on the convolutional neural network.

PloS one Oct 27, 2020
In this paper, a total of 20 sites of single nucleotide polymorphisms (SNPs) on the serotonin 3 receptor A gene (HTR3A) and B gene (HTR3B) are used for feature fusion with age, education and marital status information, and the grid search-support vec...
Age Factors Humans Adult Linear Models Male Neural Networks, Computer Marital Status Middle Aged Female Alcoholism Genotype Educational Status Support Vector Machine Young Adult
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Traditional and New Methods of Bone Age Assessment-An Overview.

Journal of clinical research in pediatric endocrinology Oct 26, 2020
Bone age is one of biological indicators of maturity used in clinical practice and it is a very important parameter of a child’s assessment, especially in paediatric endocrinology. The most widely used method of bone age assessment is by performing a...
Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Observer Variation Automation Child Development Wrist Joint Deep Learning Adolescent Child, Preschool Child Age Factors Age Determination by Skeleton Adolescent Development Hand Bones Humans Neural Networks, Computer Female Infant, Newborn Reproducibility of Results Young Adult Male Infant Diagnosis, Computer-Assisted
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Selecting the best machine learning algorithm to support the diagnosis of Non-Alcoholic Fatty Liver Disease: A meta learner study.

PloS one Oct 20, 2020
BACKGROUND & AIMS: Liver ultrasound scan (US) use in diagnosing Non-Alcoholic Fatty Liver Disease (NAFLD) causes costs and waiting lists overloads. We aimed to compare various Machine learning algorithms with a Meta learner approach to find the best ...
Glucose Non-alcoholic Fatty Liver Disease Sex Factors Male Machine Learning Humans Middle Aged Algorithms Child, Preschool Female Ultrasonography Risk Factors Age Factors Adult Cross-Sectional Studies
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Chest x-ray analysis with deep learning-based software as a triage test for pulmonary tuberculosis: a prospective study of diagnostic accuracy for culture-confirmed disease.

The Lancet. Digital health Oct 19, 2020
BACKGROUND: Deep learning-based radiological image analysis could facilitate use of chest x-rays as triage tests for pulmonary tuberculosis in resource-limited settings. We sought to determine whether commercially available chest x-ray analysis softw...
Triage Radiology Sputum Pakistan Tuberculosis, Pulmonary Mycobacterium tuberculosis Sex Factors X-Rays Lung Humans Deep Learning Software HIV Infections Prospective Studies Image Processing, Computer-Assisted Young Adult Female Body Mass Index Adult Age Factors Sensitivity and Specificity Male Middle Aged
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Risk stratification for mortality in cardiovascular disease survivors: A survival conditional inference tree analysis.

Nutrition, metabolism, and cardiovascular diseases : NMCD Oct 3, 2020
BACKGROUND AND AIMS: Efficient analysis strategies for complex network with cardiovascular disease (CVD) risk stratification remain lacking. We sought to identify an optimized model to study CVD prognosis using survival conditional inference tree (SC...
Humans Machine Learning Prognosis Age Factors Predictive Value of Tests Cause of Death Proteinuria Health Status Indicators Cardiovascular Diseases Middle Aged Risk Assessment China Female Time Factors Hyperglycemia Reproducibility of Results Risk Factors Aged Male
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Using machine learning to create prognostic systems for endometrial cancer.

Gynecologic oncology Oct 2, 2020
OBJECTIVE: We used a novel machine learning algorithm to develop a precision prognostication system for endometrial cancer.
Kaplan-Meier Estimate Female Aged Neoplasm Staging Young Adult Neoplasm Grading Adult SEER Program Survival Rate Datasets as Topic Humans Middle Aged Endometrial Neoplasms Machine Learning Risk Assessment Prognosis Adolescent United States Age Factors Endometrium
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Temporal Trends in Cervical Spine Curvature of South Korean Adults Assessed by Deep Learning System Segmentation, 2006-2018.

JAMA network open Oct 1, 2020
IMPORTANCE: The loss of the physiologic cervical lordotic curve is a common degenerative disorder known to be associated with abnormal spinal alignment. However, the changing trends among sex and age groups has not yet been well established.
Republic of Korea Female Young Adult Adult Cross-Sectional Studies Male Humans Retrospective Studies Kyphosis Lordosis Spinal Curvatures Middle Aged Deep Learning Age Factors Cervical Vertebrae Sex Factors
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Machine learning-based data analytic approaches for evaluating post-natal mouse respiratory physiological evolution.

Respiratory physiology & neurobiology Sep 30, 2020
Respiratory parameters change during post-natal development, but the nature of their changes have not been well-described. The advent of commercially available plethysmographic instruments provided improved repeatability of measurements and standardi...
Respiratory System Age Factors Plethysmography Machine Learning Mice, Inbred C57BL Animals Tidal Volume Mice Animals, Newborn Respiratory Physiological Phenomena
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