AIMC Topic: Genetic Testing
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A machine learning approach based on ACMG/AMP guidelines for genomic variant classification and prioritization.
Scientific reports
Feb 15, 2022
Genomic variant interpretation is a critical step of the diagnostic procedure, often supported by the application of tools that may predict the damaging impact of each variant or provide a guidelines-based classification. We propose the application o...
Methods to Improve Molecular Diagnosis in Genomic Cold Cases in Pediatric Neurology.
Genes
Feb 11, 2022
During the last decade, genetic testing has emerged as an important etiological diagnostic tool for Mendelian diseases, including pediatric neurological conditions. A genetic diagnosis has a considerable impact on disease management and treatment; ho...
Genetic data sharing and artificial intelligence in the era of personalized medicine based on a cross-sectional analysis of the Saudi human genome program.
Scientific reports
Jan 26, 2022
The success of the Saudi Human Genome Program (SHGP), one of the top ten genomic programs worldwide, is highly dependent on the Saudi population embracing the concept of participating in genetic testing. However, genetic data sharing and artificial i...
For whom the artificial intelligence bell tolls: preimplantation genetic testing for aneuploidy, does it toll for thee?
Fertility and sterility
Jan 20, 2022
PhenoApt leverages clinical expertise to prioritize candidate genes via machine learning.
American journal of human genetics
Jan 20, 2022
In recent years, exome sequencing (ES) has shown great utility in the diagnoses of Mendelian disorders. However, after rigorous filtering, a typical ES analysis still involves the interpretation of hundreds of variants, which greatly hinders the rapi...
An artificial intelligence model (euploid prediction algorithm) can predict embryo ploidy status based on time-lapse data.
Reproductive biology and endocrinology : RB&E
Dec 13, 2021
BACKGROUND: For the association between time-lapse technology (TLT) and embryo ploidy status, there has not yet been fully understood. TLT has the characteristics of large amount of data and non-invasiveness. If we want to accurately predict embryo p...
Artificial intelligence (AI)-assisted exome reanalysis greatly aids in the identification of new positive cases and reduces analysis time in a clinical diagnostic laboratory.
Genetics in medicine : official journal of the American College of Medical Genetics
Nov 30, 2021
PURPOSE: Artificial intelligence (AI) and variant prioritization tools for genomic variant analysis are being rapidly developed for use in clinical diagnostic testing. However, their clinical utility and reliability are currently limited. Therefore, ...
NGS and phenotypic ontology-based approaches increase the diagnostic yield in syndromic retinal diseases.
Human genetics
Aug 26, 2021
Syndromic retinal diseases (SRDs) are a group of complex inherited systemic disorders, with challenging molecular underpinnings and clinical management. Our main goal is to improve clinical and molecular SRDs diagnosis, by applying a structured pheno...
Facial recognition accuracy in photographs of Thai neonates with Down syndrome among physicians and the Face2Gene application.
American journal of medical genetics. Part A
Jul 21, 2021
Down syndrome (DS) is typically recognizable in those who present with multiple dysmorphism, especially in regard to facial phenotypes. However, as the presentation of DS in neonates is less obvious, a phenotype-based presumptive diagnosis is more ch...
Establishing a second-generation artificial intelligence-based system for improving diagnosis, treatment, and monitoring of patients with rare diseases.
European journal of human genetics : EJHG
Jul 19, 2021
Patients with rare diseases are a major challenge for healthcare systems. These patients face three major obstacles: late diagnosis and misdiagnosis, lack of proper response to therapies, and absence of valid monitoring tools. We reviewed the relevan...
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