AIMC Topic: Genetic Testing

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Towards the selection of embryos with the greatest implantation potential.

Journal of obstetrics and gynaecology : the journal of the Institute of Obstetrics and Gynaecology
Choosing the most suitable embryo remains challenging as the standard approach to select top-quality embryos for transfer rely on static morphological assessment. It is completed after fertilisation, on days 3 and 5 post oocyte retrieval and evaluate...

New Approach for Risk Estimation Algorithms of Negativeness Detection with Modelling Supervised Machine Learning Techniques.

Disease markers
gene testing is a difficult, expensive, and time-consuming test which requires excessive work load. The identification of the gene mutations is significantly important in the selection of treatment and the risk of secondary cancer. We aimed to deve...

Using chatbots to screen for heritable cancer syndromes in patients undergoing routine colonoscopy.

Journal of medical genetics
BACKGROUND: Hereditary colorectal cancer (HCRC) syndromes account for 10% of colorectal cancers but remain underdiagnosed. This feasibility project tested the utility of an artificial intelligence-based chatbot deployed to patients scheduled for colo...

Bioethics and healthcare policies. The benefit of using genetic tests of BRCA 1 and BRCA 2 in elderly patients.

The International journal of health planning and management
This study focuses on the role of bioethics in designing public healthcare policies towards elderly patients with cancer. The general overview of public administration and healthcare approach to treatment. Interpretation of how the EU public administ...

REDBot: Natural language process methods for clinical copy number variation reporting in prenatal and products of conception diagnosis.

Molecular genetics & genomic medicine
BACKGROUND: Current copy number variation (CNV) identification methods have rapidly become mature. However, the postdetection processes such as variant interpretation or reporting are inefficient. To overcome this situation, we developed REDBot as an...

Age-related Macular Degeneration: Nutrition, Genes and Deep Learning-The LXXVI Edward Jackson Memorial Lecture.

American journal of ophthalmology
PURPOSE: To evaluate the importance of nutritional supplements, dietary pattern, and genetic associations in age-related macular degeneration (AMD); and to discuss the technique of artificial intelligence/deep learning to potentially enhance research...

Virtual genetic diagnosis for familial hypercholesterolemia powered by machine learning.

European journal of preventive cardiology
AIMS: Familial hypercholesterolemia (FH) is the most common genetic disorder of lipid metabolism. The gold standard for FH diagnosis is genetic testing, available, however, only in selected university hospitals. Clinical scores - for example, the Dut...

CPEM: Accurate cancer type classification based on somatic alterations using an ensemble of a random forest and a deep neural network.

Scientific reports
With recent advances in DNA sequencing technologies, fast acquisition of large-scale genomic data has become commonplace. For cancer studies, in particular, there is an increasing need for the classification of cancer type based on somatic alteration...

Dysmorphology in a Genomic Era.

Clinics in perinatology
Dysmorphology is the practice of defining the morphologic phenotype of syndromic disorders. Genomic sequencing has advanced our understanding of human variation and molecular dysmorphology has evolved in response to the science of relating embryologi...