Personalized medicine - genomics powered by AI
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Description
New technique to begin identifying potentially problematic rare genetic variants that exist in the genomes of all people, particularly if additional genetic sequencing information is in the area of personalized medicine. The field of personalized genomics is unable to characterize the rare variants. It is because most of these abnormalities, specifically those that occur in "non-coding" parts of the genome that do not specify a protein, are not tested. Doing so would represent a major advance in a growing field that is focused on the sequencing and analysis of individuals' genomes. This research can scour reams of genetic data along with gene expression to predict the functions of variants from individual's genomes. Precision medicine blended with genomics modeling helps in identifying the personalized medicine accurately and accelerates the treatment of the disease. In this method, blood-forming stem cells are gathered from the patient to develop blood and immune cell of different types. Precision medicine blended with genomic modeling can be investigational. This type of technology helps in the revival of the patient’s condition and saving the patient from mortality. In this method, a changed viral vector referred to as lentivirus is used for adding them to the stem cells. This helps in improving gene therapy treatment. Genomic data with AI and big data helps in improving the targeted treatments to a patient using personalized medicine. Genomic data analysis helps the doctor to think from scratch about the cure using genome data. Genetic testing is used for gathering genome data. It is getting cheaper and health care centers are using it to gather huge genomic data in volumes. Health care centers are using this data with. Pharma, socioeconomic, and clinical data. Researchers and providers are the users of the data. AI in Genomics helps to improve the precision medicine or personalized medicine. The goals of the personalized medicine are improving the dis-ease diagnosis, treatment effectiveness, and prognosis. Using AI in genomics, personalized medicine techniques help in detecting patient’s variability in genes. The environmental factors can be isolated from the genetic analysis using the symptoms of the patient. Using this analysis, doctors can customize the treatment and prevent the disease growing in the patient.
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