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AI-based analysis of fetal growth restriction in a prospective obstetric cohort quantifies compound risks for perinatal morbidity and mortality and identifies previously unrecognized high risk clinical scenarios.
BMC Pregnancy Childbirth
January 2025
Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, University of Utah Health, 30 N. Mario Capecchi Dr., Level 5 South, Salt Lake City, UT, 84132, USA.
Background: Fetal growth restriction (FGR) is a leading risk factor for stillbirth, yet the diagnosis of FGR confers considerable prognostic uncertainty, as most infants with FGR do not experience any morbidity. Our objective was to use data from a large, deeply phenotyped observational obstetric cohort to develop a probabilistic graphical model (PGM), a type of "explainable artificial intelligence (AI)", as a potential framework to better understand how interrelated variables contribute to perinatal morbidity risk in FGR.
Methods: Using data from 9,558 pregnancies delivered at ≥ 20 weeks with available outcome data, we derived and validated a PGM using randomly selected sub-cohorts of 80% (n = 7645) and 20% (n = 1,912), respectively, to discriminate cases of FGR resulting in composite perinatal morbidity from those that did not.
Background: Fetal growth restriction (FGR) is a leading risk factor for stillbirth, yet the diagnosis of FGR confers considerable prognostic uncertainty, as most infants with FGR do not experience any morbidity. Our objective was to use data from a large, deeply phenotyped observational obstetric cohort to develop a probabilistic graphical model (PGM), a type of "explainable artificial intelligence (AI)", as a potential framework to better understand how interrelated variables contribute to perinatal morbidity risk in FGR.
Methods: Using data from 9,558 pregnancies delivered at ≥ 20 weeks with available outcome data, we derived and validated a PGM using randomly selected sub-cohorts of 80% (n = 7645) and 20% (n = 1,912), respectively, to discriminate cases of FGR resulting in composite perinatal morbidity from those that did not.
Epidermal Growth Factor Receptor (EGFR) and SMAD4 negatively correlated in the progression of gallbladder cancer in Eastern Indian patients.
BMC Gastroenterol
December 2024
Human Genetics Unit, Indian Statistical Institute, 203, B. T. Road, Kolkata, 700108, India.
Background And Introduction: Two and half percent of the Indian population suffer from gallbladder cancer (GBC). The primary factors that lead GBC are associated with mutation of several protooncogenes such as EGFR, ERBB2, Myc, and CCND1 along with dysregulation of several tumor suppressor genes such as SMAD4 and CDKN2A. Bacterial infection caused by S.
View Article and Find Full Text PDFExploring the association between individual, family, and program characteristics and change in health outcomes 12 months after enrollment into the CANadian Pediatric Weight management Registry (CANPWR).
Int J Obes (Lond)
January 2025
Department of Pediatrics, McMaster University, Hamilton, ON, Canada.
Objectives: To examine individual, family, and program characteristics associated with changes in anthropometric and cardiometabolic health indicators in children with overweight or obesity after participating in multidisciplinary obesity management for 12 months.
Methods: Participants included children 2-17 years old with overweight or obesity enrolled in the CANadian Pediatric Weight Management Registry (CANPWR). Multiple linear regression analyses were conducted to investigate the associations between individual, family, and program characteristics and changes in anthropometry (WHO BMI z-score) and cardiometabolic health indicators (systolic and diastolic blood pressure; fasting and 2-h glucose post-oral glucose tolerance test (OGTT); high density lipoprotein- (HDL) and non-HDL cholesterol and fasting triglycerides).
Maple syrup urine disease diagnosis in Brazilian patients by massive parallel sequencing.
Mol Genet Metab
October 2024
BRAIN Laboratory (Basic Research and Advanced Investigations in Neurosciences), Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil; Graduate Program in Genetics and Molecular Biology, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil; Graduate Program in Medicine: Medical Sciences, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil; Clinical Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil; Medical Genetics Service, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil; Department of Genetics, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil; InRaras, National Institute of Rare Diseases, Brazil.
Biallelic pathogenic variants cause maple syrup urine disease (MSUD) in one of the branched-chain α-keto acid dehydrogenase (BCKDH) complex genes (BCKDHA, BCKDHB, DBT, DLD, and PPM1K) leading to the accumulation of leucine, isoleucine, and valine. This study aimed to perform a molecular diagnosis of Brazilian patients with MSUD using gene panels and massive parallel sequencing. Eighteen Brazilian patients with a biochemical diagnosis of MSUD were analyzed by massive parallel sequencing in the Ion PGM Torrent Server using a gene panel with the BCKDHA, BCKDHB, and DBT genes.
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