AIMC Topic: Genetic Testing
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What could be the role of genetic tests and machine learning of AXIN2 variant dominance in non-syndromic hypodontia? A case-control study in orthodontically treated patients.
Progress in orthodontics
Aug 26, 2024
BACKGROUND: Hypodontia is the most prevalent dental anomaly in humans, and is primarily attributed to genetic factors. Although genome-wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNP) associated with hypodontia, g...
Machine learning analysis of oxidative stress-related phenotypes for specific gene screening in ovarian cancer.
Environmental toxicology
Aug 20, 2024
BACKGROUND: Oxidative stress serves a crucial role in tumor development. However, the relationship between ovarian cancer and oxidative stress remains unknown. We aimed to create an oxidative stress-related prognostic signature to enhance the prognos...
Factors affecting biochemical pregnancy loss (BPL) in preimplantation genetic testing for aneuploidy (PGT-A) cycles: machine learning-assisted identification.
Reproductive biology and endocrinology : RB&E
Aug 8, 2024
PURPOSE: To determine the factors influencing the likelihood of biochemical pregnancy loss (BPL) after transfer of a euploid embryo from preimplantation genetic testing for aneuploidy (PGT-A) cycles.
Improving the Detection of Potential Cases of Familial Hypercholesterolemia: Could Machine Learning Be Part of the Solution?
Journal of the American Heart Association
Jun 15, 2024
BACKGROUND: Familial hypercholesterolemia (FH), while highly prevalent, is a significantly underdiagnosed monogenic disorder. Improved detection could reduce the large number of cardiovascular events attributable to poor case finding. We aimed to ass...
Enhancing clinical utility: deep learning-based embryo scoring model for non-invasive aneuploidy prediction.
Reproductive biology and endocrinology : RB&E
May 22, 2024
BACKGROUND: The best method for selecting embryos ploidy is preimplantation genetic testing for aneuploidies (PGT-A). However, it takes more labour, money, and experience. As such, more approachable, non- invasive techniques were still needed. Analys...
Applying Artificial Intelligence for Phenotyping of Inherited Arrhythmia Syndromes.
The Canadian journal of cardiology
Apr 24, 2024
Inherited arrhythmia disorders account for a significant proportion of sudden cardiac death, particularly among young individuals. Recent advances in our understanding of these syndromes have improved patient diagnosis and care, yet certain clinical ...
An AI-based approach driven by genotypes and phenotypes to uplift the diagnostic yield of genetic diseases.
Human genetics
Mar 23, 2024
Identifying disease-causing variants in Rare Disease patients' genome is a challenging problem. To accomplish this task, we describe a machine learning framework, that we called "Suggested Diagnosis", whose aim is to prioritize genetic variants in an...
Improving newborn screening in India: Disease gaps and quality control.
Clinica chimica acta; international journal of clinical chemistry
Mar 21, 2024
In India, newborn screening (NBS) is essential for detecting health problems in infants. Despite significant progress, significant gaps and challenges persist. India has made great strides in genomics dueto the existence of the National Institute of ...
Applying data science methodologies with artificial intelligence variant reinterpretation to map and estimate genetic disorder prevalence utilizing clinical data.
American journal of medical genetics. Part A
Jan 2, 2024
Data science methodologies can be utilized to ascertain and analyze clinical genetic data that is often unstructured and rarely used outside of patient encounters. Genetic variants from all genetic testing resulting to a large pediatric healthcare sy...
The ENGAGE study: evaluation of a conversational virtual agent that provides tailored pre-test genetic education to cancer patients.
Journal of cancer survivorship : research and practice
Dec 8, 2023
PURPOSE: Novel approaches are needed to ensure all patients with cancer have access to quality genetic education before genetic testing to enable informed treatment decisions. The purpose of this study was to test the use of an artificial intelligenc...
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