Good health is a fundamental need for all of us. Hence, it’s no surprise that the total market size of healthcare is huge. Developed countries typically spend between 9% and 14% of their total GDP on healthcare.
The digital transformation in the healthcare sector is still in its early stages. A prominent example is the Electronic Health Record (EHR) in particular, and, in general poor quality of data. Other obstacles include data privacy concerns, risk of bias, lack of transparency, as well as legal and regulatory risks. Although all these matters have to be addressed in a Digital Strategy, the implementation of Artificial Intelligence (AI) should not hesitate!
AI has to potential to save millions of lives by applying complex algorithms to emulate human cognition in the analysis of complicated medical data. AI furthermore simplifies the lives of patients, doctors, and hospital administrators by performing or supporting tasks that are typically done by humans, but more efficiently, more quickly and at a fraction of the cost. The applications for AI in healthcare are wide-ranging. Whether it’s being used to discover links between genetic codes, to power surgical robots or even to maximize hospital efficiency, AI is reinventing modern healthcare through machines that can predict, comprehend, learn and act.
Let’s have a look at ten of the most straightforward use cases for AI in healthcare that should be considered for any Digital Strategy:
AI can mine demographic, geographic, laboratory and doctor visits, and historic claims data to predict an individual patient’s likelihood of developing a condition. Using this data predictive models can suggest the best possible treatment regimens and success rate of certain procedures.
AI brings in advanced insights into the medical imagery specifically the radiological images. Using AI providers can gain insights and conduct automatic, quantitative analysis such as identification of tumors, fast radiotherapy planning, precise surgery planning, and navigation, etc.
AI helps to solve patient registry mapping issues for and help the Human Genome Project map complicated genomic sequences to identify the link to diseases like Alzheimer’s.
