Show notes
Dr. Gary Fogel, CEO of Natural Selection Inc from the United States participates in Risk Roundup to discuss Machine Learning for Medical Diagnosis.
Machine Learning for Medical Diagnosis
Medicine, medical care, disease care, and healthcare are rapidly emerging to be human-machine collaboration. At this point, we see both humans and machines performing tasks at which they are good. While this symbiotic relationship is still at an early stage, as machine learning and deep learning systems develop and evolve, it is expected that machines will increasingly assist humans with those tasks at which they are not very good.
So, what are we humans good at? It seems we, humans, are good at processing information from our senses. We are also very good at perceiving human emotions. However, we are not so good at remembering things, searching for and organizing data– and we are also not good at correlating and reasoning data as well.
This is where machine learning systems will add tremendous value. Machine learning systems will make physicians, providers, and practitioners faster and smarter in their diagnoses. As a result, this will reduce uncertainty in their decisions, thereby reducing costs and risks and saving valuable time. This is welcoming as there is an increasing concern that manual medical diagnostic practices, which are driven largely by human intelligence, are no longer sufficient to effectively perform complex disease diagnostic tasks on their own, in a timely and cost-effective manner.
From across nations, there are numerous reports emerging that machine learning has convincingly penetrated complex processes of medicine, especially medical diagnosis. As machine learning seems to be on its way to transforming the world of medicine and medical diagnosis, it is changing the fundamentals of not only disease diagnosis and care, but also healthcare.
As we speak, machine learning/deep learning and AI are transforming the disease care/healthcare industry. While they improve patient outcomes and change the way doctors think about providing disease care as well as health care, they also bring complex challenges and security risks that need to be managed effectively.
It is time to evaluate machine learning for medical diagnosis.
For more please watch the Risk Roundup Webcast or hear the Risk Roundup Podcast
About the Guest
Gary Fogel is Chief Executive Officer of Natural Selection, Inc. He has spent most of his career as a data scientist applying computational intelligence and machine learning to medicine, industry, and defense.
He is also Adjunct Faculty at San Diego State University, and co-founder and managing director of Theragence, Inc. He is currently Editor-in-Chief of the journal BioSystems, serves on the Administrative Committee for the IEEE Computational Intelligence Society, and is a Fellow of the IEEE.
He received his B.A. in biology from the University of California, Santa Cruz, and Ph.D. in biology from the University of California, Los Angeles.
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