How Artificial Intelligence and Precision Medicine Enhance Personalized Treatment

Artificial Intelligence increases the therapeutic power of doctors with applications aimed at determining the disease risks of the person, which is the aim of Precision Medicine  , and realizing personalized prevention and treatment methods.

Artificial intelligence uses complex computation and inferences to generate insights and enable the system to learn and reason. Research shows that precision medicine, genomic and non-genomic markers, combined with information from clinical history and lifestyles, facilitate personalized treatment and predict the course and duration of disease.

Complex Problems of Artificial Intelligence and Precision Medicine

Applications of artificial intelligence (AI) and precision medicine indicate that a new era will begin in healthcare. Precision medicine methods describe the phenotypes of patients who are less responsive to treatment or unique health needs. AI leverages complex computation and inferences to generate insights, enables system reasoning and learning, and empowers clinicians’ decision making through augmented intelligence.

The most important challenge facing precision medicine is to make available genomic and non-genomic markers from patient symptoms, clinical history and lifestyles for personalized treatment. Artificial intelligence precision medicine has significant potential to solve the most complex problems in personalized medicine. Many solutions are being developed for treatment, determination and estimation of disease risk using clinical, genomic or social and behavioral determinants and other variables.

Artificial Intelligence Assisted Precision medicine, Personalized Treatment

Artificial intelligence approaches that excel at discovering complex relationships between multiple factors provide such opportunities. A study from Vanderbilt found early examples of combining HIMS and genetic data with positive results in cardiovascular disease prediction. Activating phenotype features with Artificial Intelligence through HIMS or images and matching these features with genetic variants provide faster diagnosis of genetic diseases. For example, accurate and rapid diagnosis for severely ill infants suspected of having a genetic disease can be achieved using rapid whole-genome sequencing and automated phenotyping with NLP enabled.

The power of precision medicine to customize care, in particular, the emergence of genotyping, the global use of electronic health records (ESCs) has created an opportunity to generate new phenotypes. These phenotypes, combined with information from IHC, will improve the diagnosis and treatment of diseases.

The first successful example of artificial intelligence in image recognition was radiogenomics. As a new field of precision medicine research, radiogenomics focuses on establishing associations between cancer imaging features and gene expression to predict a patient’s risk of developing toxicity following radiotherapy.

Complex diseases such as cardiovascular disease often involve interactions between gender, genetics, lifestyle and environmental factors.

The Importance of Genome for Precision Medicine

Genotype-based therapy is perhaps the best-studied impact of precision medicine in therapy today. However, machine learning algorithms need to be developed to predict which patients will need which drug in the light of genomic information. Genotyping must be done first to customize drugs and dosages. It was among the first examples of convergence between Artificial Intelligence and precision medicine, as AI techniques proved useful for efficient genome interpretation.

Clinicians have used genotype information as a guide to help determine the correct dose of Warfarin. Precision medicine perhaps first demonstrated its power in prescriptions based on genome information. Precision oncology treatments rely heavily on patient genomic data to make treatment decisions. Whole genome sequencing has already improved our understanding of tumors; Unprecedented molecular detail combined with next-generation drug development has enabled high-throughput targeted therapy.

Is the treatment of chronic diseases and incurable diseases close?

It will be possible to prevent and cure diseases for which there is no definitive treatment, with next-generation sequencing and genetic testing. We are entering an era when research in both artificial intelligence and precision medicine will be powered by personalized medical diagnosis and therapeutic information. Advances in artificial intelligence and Precision Medicine Cardiovascular medicine has been using predictive applications for many years. Thus, the person’s risk of contracting the disease can be estimated. Recent studies have revealed methods for predicting heart failure and other serious cardiac events in asymptomatic individuals.

At the same time, cancer drug development is advancing rapidly thanks to precision medicine, and drugs are matched for individual treatments of selected patients. The use of Artificial Intelligence/Machine Learning has already proven successful in selecting drug combinations and making recommendations for drugs based on the patient’s own biopsy.
Identifying reliable drug targets and driver genes for personalized medicine is crucial in cancer treatment. Artificial Intelligence/Machine Learning has begun to play a role in creating new drug candidates and redesigning existing drugs.

The synergy between the two forces and their impact on the health system is in line with the ultimate goal of prevention and early detection of diseases that affect the individual, which can ultimately reduce the burden of disease for the public and therefore the cost of preventable diseases.