Artificial Intelligence runs the gamut from virtual personalassistants to intelligent automation and cognitive computing using machinelearning and deep learning algorithms.
Applications of AI are now being appliedto large volumes of data from increasingly diverse sources. The results areguiding clinicians on basically everything from drug discovery to diagnosis of variousailments. AI helps in increasing accuracy of diagnosis and efficiency oftreatment.
Precision medicine is ‘an emerging approach for diseasetreatment and prevention that takes into account individual variability ingenes, environment and lifestyle for each person.’ This approach allows doctorsand researchers to predict more accurately which treatment or preventionstrategies for a particular disease will work. It requires significantcomputing power; algorithms that can learn by themselves at an unprecedentedrate; and generally an approach that uses the cognitive capabilities ofphysicians on a new scale.
Precision medicine requires a myriad of disruptive technologiesto be implemented into developing treatments. Practicing medicine is allowingcare, however data analysis no matter how advanced it is cannot replace the patient-doctor relationship. In order to keep that human touch in medicine in a waythat the opportunities of treating the right people with the most personalizedtherapies are augmented, one preparation might be useful: For getting thepatients accustomed to AI and discovering its benefits – e.
g with the help ofcogni toys which support the cognitive development of small children with thehelp of AI.AIalso has serious limitations in healthcare. Forecasting and prediction are medicatedbased on precedence in the case of machine learning but algorithms can beunderperforming in novel cases of drug side effects or treatment resistancewhere there is no prior example to build on. Hence, AI may not replace tacitknowledge that cannot be codified easily