Practical Implementations of AI in Precision Medicine

Healthcare AI applications and examples hold the promise of affordable healthcare, improved success rates, effective clinical trials, and improved quality of life. One of the most valuable examples of AI in healthcare is precision medicine, now known as the paradigm-shifting practice of healthcare. Precision medicine is based on the abundance of data gathered from many disruptive technological innovations, including patient use of health sensors at home, cheap sequencing of genomes, and advanced biotechnology. Precision medicine refers to “adjustment of medical treatment to each patient’s individual characteristics.” Medical practices are now shifting rapidly from decision-making based on a few seemingly overlapping patient features to a more personalized format. 

Precision medicine is dependent on advanced deep learning supercomputing algorithms and therefore uses physicians ‘ cognitive abilities on a new scale. One of the challenges in this day and age of easy access to genomic data is to search for genetic variants that increase the risk of disease. Intel has developed a deep learning algorithm in collaboration with the Scripps Research Institute, CA, USA that could detect 23 patients with increased risk of cardiovascular disease, unidentified by conventional statistical methods, with 85% accuracy. IBM Watson and Google DeepMind are the leaders in the field of mining medical records, with the ultimate goal of creating a “cognitive assistant” equipped with a range of clinical, analytical and reasoning skills.

Keep watching this space for more such interesting developments in the field of healthcare technology.

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