Kamal Jain* and Vinita Shah
Precision medicine is an important and growing area of research, development and healthcare for the diagnosis of diseases and patients precare. It involves analysis of a patient's personal data, genetic information, circumstances to diagnose and cure the disease. It allows researchers to design and develop the medication for prevention of specific viruses. It has the potential to improvise the traditional symptom driven retrospective practice of medicine, by allowing earlier interventions with advanced diagnostics, which can further be used for tailoring personalized treatments. Identification of the pathway for developing a personalized medicine involves analyzing comprehensive patient information along with broader aspects to monitor and distinguish between healthy and sick people, which will lead to a better understanding of biological indicators that can signal shifts in health. In order to positively impact the patient’s health and to provide real time decision support, it is vital to leverage the power of electronic health records by integrating disparate data sources and discovering patient-specific patterns of disease progression. The goal of which is to use multiple types of data and classify patients into precise groups that will benefit from a given treatment approach. In this article, we will focus on various machine learning, deep learning models, and applications of AI which can pave the way for a new data-centric era of discovery in healthcare. In this article, we will focus on various machine learning, deep learning models, and applications of AI which can pave the way for a new data-centric era of discovery in healthcare.
