The U.S. healthcare industry has more than 12 million diagnostic errors each year. Life expectancy is not improving, costs are too high, and physicians are overworked. And there is more medical data per patient than ever before. The good news, however, is that from medical imaging to analyzing genomes to discovering new drugs, artificial intelligence (AI) in healthcare is getting better and more sophisticated at doing what humans do, and doing it more accurately, more quickly, and with lower cost. A McKinsey review in 2018 predicted healthcare as one of the top five industries with more than 50 use cases that would involve AI, and over $1 billion has already been raised in startup equity.
Doctors are now making faster, more accurate diagnoses thanks to AI. Of heart patients, 61% are avoiding invasive angiograms, cutting treatment costs by 26%. AI is reducing diagnosis errors in breast cancer patients by 85% and enabling MRIs to accelerate image reconstruction by a factor of 100—with 5-times greater accuracy.
AI allows drug researchers to expedite discovery and development and can reduce the cost of bringing new drugs to market during their 12–14 years of development. AI analyzes millions of molecules to quickly identify potential drugs and lower development costs, and researchers of Alzheimer’s, cancer, and multiple sclerosis drugs report a tenfold increase in their productivity.
As a result of AI, healthcare costs are falling and outcomes are improving. The cost of AI-automated breast cancer risk assessments is 5% lower compared with current genomic tests. Two million stroke patient neurons are being saved each minute by rapid AI diagnoses, and tens of millions of healthcare professionals globally will use AI and retina imaging to quickly detect countless medical conditions.
Today’s data visionaries are joining NetApp and NVIDIA to apply AI and deep learning to healthcare’s greatest challenges. Together, we are accelerating medical discoveries and improving patient care.
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