Technology Advisor – The importance of artificial intelligence in health care
May 17, 2017
By Bipin Thomas
Artificial intelligence (AI) is defined as the science and engineering of creating intelligent computer systems that are capable of performing tasks without receiving instructions directly from humans.
These computer systems use a number of different algorithms and decision-making capabilities, as well as vast amounts of data, to provide a solution or response to a request. The applications of AI have been proliferating at a much faster pace across all industries, including health care.
The health care startups entering the artificial intelligence space increased in recent years. Health care deals focused on AI startups went up from less than 20 in 2012 to nearly 70 in 2016. Today, there are hundreds of companies that are applying machine learning algorithms and predictive analytics to reduce drug discovery times, provide virtual assistance to patients and diagnose ailments by processing medical images, among other things. By 2020, AI systems will be involved in everything from population health management to digital avatars capable of interacting with patients over video.
IBM’s Watson is the most popular AI-driven system that has been tackling cancer diagnostics on par with human physicians. Google’s DeepMind is revolutionizing eye care in the U.K. Both of these AI systems use deep learning, a concept loosely mirroring how our own brains work by having AI software analyze exorbitant amounts of data and uncover patterns — which is particularly applicable in diagnostics. Whenever a new technology enters health care, there are a number of challenges it faces. Common setbacks of AI in health care include a lack of electronic data exchange, regulatory compliance requirements and patient and provider adoption. AI has come across all of these issues, narrowing down the areas in which it can succeed.
Artificial intelligence is making its way into the realm of modern health care. While AI won’t be replacing physicians, it will provide doctors with intelligent tools to assess patients more efficiently and reliably. AI is already involved in mining medical data, diagnosing medical images and analyzing genomics-based data for personalized medicine. Hospitals can now efficiently compare a single patient’s tests and history with data from a vast population of other patients. There is tremendous progress in automating the analysis of MRIs, CT scans and X-rays to assist physicians in making a diagnosis. Others are utilizing deep learning to create genetic interpretation engines to identify cancer-causing mutations in patient genomes, bringing to life the concept of personalized medicine.
Artificial intelligence-driven chatbots and virtual assistants are widening the reach of video telemedicine options. In this case, diagnosis can be enabled by machine learning and then trained by artificial intelligence. There are several companies launching these AI capabilities in their telemedicine platforms to triage the symptoms before connecting the user with a physician over phone or video.
Care delivery
Artificial intelligence can not only improve care delivery, but also assist in clinician decision-making and operational efficiency, amplifying the impact of each individual practitioner. AI helps streamline hospital operations in emergency rooms, operating rooms and inpatient wards. It also analyzes disparate data sources to accurately triage and apply interventions to the highest-risk patients. AI not only helps physicians, but also patients. Recent studies have determined that 50 percent of patients have difficulty with medication adherence. AI-enabled computer vision techniques to enable smart-phones to recognize faces and medications helped lower the cost and improve the effectiveness of tracking and adherence programs.
Artificial intelligence-powered patient coaching will allow a provider or care manager to manage more than 1,000 patients simultaneously rather than 50 to 100, offering an increase in labor leverage. Drug discovery companies can now utilize AI systems to de-risk the drug development process, enabling powerful and proprietary new combination therapies, as well as individualized treatment with unprecedented efficacy and safety. It significantly lowers the spend for each drug brought to market.
AI will continue to revolutionize medicine and care delivery for years to come. Physicians are trying to incorporate these technologies into their regular practice. When AI is fully integrated into medicine, we will see the full potential for the technology in terms of lending itself to more efficient and accurate diagnostics, from routine checkups to more specialized areas.
About the author: Bipin Thomas is a renowned business-technology innovator and thought leader on consumer-centric health care transformation. Thomas is a board member of HealthCare Business News magazine and strategic advisor to Health- Tap. Thomas is a senior executive at Flex, where he is leading business innovation by enabling intelligent products and connecting all stakeholders across industries. Thomas is a former senior executive at Accenture and UST Global, where he implemented strategic digital initiatives across the care continuum.
Artificial intelligence (AI) is defined as the science and engineering of creating intelligent computer systems that are capable of performing tasks without receiving instructions directly from humans.
These computer systems use a number of different algorithms and decision-making capabilities, as well as vast amounts of data, to provide a solution or response to a request. The applications of AI have been proliferating at a much faster pace across all industries, including health care.
The health care startups entering the artificial intelligence space increased in recent years. Health care deals focused on AI startups went up from less than 20 in 2012 to nearly 70 in 2016. Today, there are hundreds of companies that are applying machine learning algorithms and predictive analytics to reduce drug discovery times, provide virtual assistance to patients and diagnose ailments by processing medical images, among other things. By 2020, AI systems will be involved in everything from population health management to digital avatars capable of interacting with patients over video.
IBM’s Watson is the most popular AI-driven system that has been tackling cancer diagnostics on par with human physicians. Google’s DeepMind is revolutionizing eye care in the U.K. Both of these AI systems use deep learning, a concept loosely mirroring how our own brains work by having AI software analyze exorbitant amounts of data and uncover patterns — which is particularly applicable in diagnostics. Whenever a new technology enters health care, there are a number of challenges it faces. Common setbacks of AI in health care include a lack of electronic data exchange, regulatory compliance requirements and patient and provider adoption. AI has come across all of these issues, narrowing down the areas in which it can succeed.
Artificial intelligence is making its way into the realm of modern health care. While AI won’t be replacing physicians, it will provide doctors with intelligent tools to assess patients more efficiently and reliably. AI is already involved in mining medical data, diagnosing medical images and analyzing genomics-based data for personalized medicine. Hospitals can now efficiently compare a single patient’s tests and history with data from a vast population of other patients. There is tremendous progress in automating the analysis of MRIs, CT scans and X-rays to assist physicians in making a diagnosis. Others are utilizing deep learning to create genetic interpretation engines to identify cancer-causing mutations in patient genomes, bringing to life the concept of personalized medicine.
Artificial intelligence-driven chatbots and virtual assistants are widening the reach of video telemedicine options. In this case, diagnosis can be enabled by machine learning and then trained by artificial intelligence. There are several companies launching these AI capabilities in their telemedicine platforms to triage the symptoms before connecting the user with a physician over phone or video.
Care delivery
Artificial intelligence can not only improve care delivery, but also assist in clinician decision-making and operational efficiency, amplifying the impact of each individual practitioner. AI helps streamline hospital operations in emergency rooms, operating rooms and inpatient wards. It also analyzes disparate data sources to accurately triage and apply interventions to the highest-risk patients. AI not only helps physicians, but also patients. Recent studies have determined that 50 percent of patients have difficulty with medication adherence. AI-enabled computer vision techniques to enable smart-phones to recognize faces and medications helped lower the cost and improve the effectiveness of tracking and adherence programs.
Artificial intelligence-powered patient coaching will allow a provider or care manager to manage more than 1,000 patients simultaneously rather than 50 to 100, offering an increase in labor leverage. Drug discovery companies can now utilize AI systems to de-risk the drug development process, enabling powerful and proprietary new combination therapies, as well as individualized treatment with unprecedented efficacy and safety. It significantly lowers the spend for each drug brought to market.
AI will continue to revolutionize medicine and care delivery for years to come. Physicians are trying to incorporate these technologies into their regular practice. When AI is fully integrated into medicine, we will see the full potential for the technology in terms of lending itself to more efficient and accurate diagnostics, from routine checkups to more specialized areas.
About the author: Bipin Thomas is a renowned business-technology innovator and thought leader on consumer-centric health care transformation. Thomas is a board member of HealthCare Business News magazine and strategic advisor to Health- Tap. Thomas is a senior executive at Flex, where he is leading business innovation by enabling intelligent products and connecting all stakeholders across industries. Thomas is a former senior executive at Accenture and UST Global, where he implemented strategic digital initiatives across the care continuum.