AIMC Topic: Body Mass Index

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Physical Features and Vital Signs Predict Serum Albumin and Globulin Concentrations Using Machine Learning.

Asian Pacific journal of cancer prevention : APJCP Feb 1, 2021
OBJECTIVE: Serum protein concentrations are diagnostically and prognostically valuable in cancer and other diseases, but their measurement via blood test is uncomfortable, inconvenient, and costly. This study investigates the possibility of predictin...
Machine Learning Female Adult Male Middle Aged Humans Sex Factors Body Height Vital Signs Serum Albumin Serum Globulins China Body Mass Index Age Factors Predictive Value of Tests Body Weight
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Ranking of a wide multidomain set of predictor variables of children obesity by machine learning variable importance techniques.

Scientific reports Jan 21, 2021
The increased prevalence of childhood obesity is expected to translate in the near future into a concomitant soaring of multiple cardio-metabolic diseases. Obesity has a complex, multifactorial etiology, that includes multiple and multidomain potenti...
Humans Machine Learning Female Risk Factors Body Mass Index Metabolic Diseases Spain Life Style Male Diet Exercise Child Pediatric Obesity
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Deep Learning Image Analysis of Benign Breast Disease to Identify Subsequent Risk of Breast Cancer.

JNCI cancer spectrum Jan 11, 2021
BACKGROUND: New biomarkers of risk may improve breast cancer (BC) risk prediction. We developed a computational pathology method to segment benign breast disease (BBD) whole slide images into epithelium, fibrous stroma, and fat. We applied our method...
Menarche Elasticity Analysis of Variance Menopause Body Size Breast Diseases Adult Breast Neoplasms Middle Aged Risk Assessment Case-Control Studies Deep Learning Cohort Studies Body Mass Index Predictive Value of Tests Breast Neural Networks, Computer Female Parity Risk Factors Aged Humans
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Body Mass Index Variable Interpolation to Expand the Utility of Real-world Administrative Healthcare Claims Database Analyses.

Advances in therapy Jan 11, 2021
INTRODUCTION: Administrative claims data provide an important source for real-world evidence (RWE) generation, but incomplete reporting, such as for body mass index (BMI), limits the sample sizes that can be analyzed to address certain research quest...
Humans Body Mass Index Machine Learning Algorithms Delivery of Health Care Databases, Factual ROC Curve
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Early response to SPN-812 (viloxazine extended-release) can predict efficacy outcome in pediatric subjects with ADHD: a machine learning post-hoc analysis of four randomized clinical trials.

Psychiatry research Jan 5, 2021
Machine learning (ML) was used to determine whether early response can predict efficacy outcome in pediatric subjects with ADHD treated with SPN-812. We used data from four Phase 3 placebo-controlled trials of 100- to 600-mg/day SPN-812 (N=1397; 6-17...
Central Nervous System Stimulants Delayed-Action Preparations Attention Deficit Disorder with Hyperactivity Adolescent Viloxazine Child Humans Treatment Outcome Machine Learning Body Mass Index Randomized Controlled Trials as Topic Female Dose-Response Relationship, Drug Double-Blind Method Male Body Weight Clinical Trials as Topic Drug Administration Schedule
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Early Predictors of Gestational Diabetes Mellitus in IVF-Conceived Pregnancies.

Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists Dec 17, 2020
OBJECTIVE: Gestational diabetes mellitus (GDM) is associated with adverse maternal and fetal outcomes. This study aimed to identify early and reliable GDM predictors that would enable implementation of preventive and management measures.
Glucose Tolerance Test Polycystic Ovary Syndrome Aged Humans Blood Glucose Prospective Studies Fertilization in Vitro Pregnancy Female Body Mass Index Diabetes, Gestational
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Predicting Postoperative Mortality After Metastatic Intraspinal Neoplasm Excision: Development of a Machine-Learning Approach.

World neurosurgery Nov 16, 2020
OBJECTIVE: Mortality following surgical resection of spinal tumors is a devastating outcome. Naïve Bayes machine learning algorithms may be leveraged in surgical planning to predict mortality. In this investigation, we use a Naïve Bayes classificatio...
Odds Ratio Serum Albumin Machine Learning Mortality Female Preoperative Care Aged Laminectomy Body Mass Index Pulmonary Disease, Chronic Obstructive Bayes Theorem Blood Coagulation Disorders Male Middle Aged Humans Ascites Risk Assessment Hypoalbuminemia Smoking Respiration, Artificial Dyspnea Metastasectomy Weight Loss Spinal Neoplasms Hypertension Multivariate Analysis
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Host variables confound gut microbiota studies of human disease.

Nature Nov 4, 2020
Low concordance between studies that examine the role of microbiota in human diseases is a pervasive challenge that limits the capacity to identify causal relationships between host-associated microorganisms and pathology. The risk of obtaining false...
Humans Machine Learning Data Analysis Female Aged Aged, 80 and over Young Adult Adult Male Middle Aged Gastrointestinal Motility Alcohol Drinking Body Mass Index Diet Disease Gastrointestinal Microbiome Case-Control Studies Life Style RNA, Ribosomal, 16S Feces Confounding Factors, Epidemiologic Residence Characteristics ROC Curve Area Under Curve Diabetes Mellitus, Type 2
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Personalized computed tomography - Automated estimation of height and weight of a simulated digital twin using a 3D camera and artificial intelligence.

RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin Nov 3, 2020
PURPOSE:  The aim of this study was to develop an algorithm for automated estimation of patient height and weight during computed tomography (CT) and to evaluate its accuracy in everyday clinical practice.
Humans Tomography, X-Ray Computed Artificial Intelligence Imaging, Three-Dimensional Algorithms Abdomen Computer Simulation Body Mass Index Precision Medicine
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A Three-Dimensional Deep Convolutional Neural Network for Automatic Segmentation and Diameter Measurement of Type B Aortic Dissection.

Korean journal of radiology Nov 3, 2020
OBJECTIVE: To provide an automatic method for segmentation and diameter measurement of type B aortic dissection (TBAD).
Body Mass Index Humans Aortic Dissection Retrospective Studies Adult Aorta Female Computed Tomography Angiography Male Middle Aged Deep Learning Imaging, Three-Dimensional
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