For most, healthcare equals headaches. Whether it's paying your monthly premium or visiting a loved one in the hospital, the subject can be a real downer. But emergent technology could change the way we interact with our health. So let's talk about something lighter: how AI could make the entire healthcare experience more tolerable for all parties.
We asked these industry insiders about the state of AI in healthcare today. Here's what they said:
1. Randy Hamlin, Vice President and Segment Leader for Point-of-Care Ultrasound at Philips
“In general, people are becoming more comfortable with AI. They’re starting to see it in autonomous cars, retail and healthcare products, though healthcare is slow to adopt new technology.
AI in healthcare is in its infancy, but there’s so much potential. In ultrasound, for example, AI programs can enable much better imaging, improved clinical workflows, aid healthcare professionals in detection and diagnosis of certain clinical conditions, and in general further enabling overall clinical utility of ultrasound devices in various clinical use scenarios and environment. And better imaging can make the difference between aiding the healthcare professionals in detecting and diagnosis of a life-threatening problem.
Because of this, there’s a real urgency to increase the rate of adoption of AI in healthcare so healthcare professionals can use the power of the technology to deliver better outcomes for patients.”
2. Laura Marble, VP, IT at Blue Cross Blue Shield of Michigan
“Clinical applications of AI are the most common use in these early stages of AI adoption. They provide medical professionals with a greater level of precision and accuracy when diagnosing and treating patients. Hospitals are prioritizing clinical investments upfront to help improve the quality of care. Health-related AI has also found a foothold amongst consumers via wearable technologies, which can help patients manage or monitor chronic conditions in real-time. Even phone apps that remind patients to take medicine or allow them to easily schedule appointments are indicative traits of AI adoption in health care.”
3. David Maman, CEO, CTO, & Co-founder of Binah.ai
“I think that in general, everyone acknowledges that AI can be used in all facets of the healthcare system, from accelerating diagnoses to preventing the spread of disease. Still, some see AI as a threat, as this monster machine that comes in to cut everyone’s jobs. This cannot be farther from the truth. AI in healthcare supports, enhances, and aids medical staff in analyzing patients’ data faster and better, boosting their decision making, freeing their time from repetitive, administrative work, and letting them spend more quality time with their patients. The human element is and will also be vital in healthcare. No machine can replace this.”
4. Russell Olsen, VP of Innovation and Project Management at WebPT
“AI is already transforming healthcare and is changing the future of health monitoring, disease detection and diagnosis, drug development, treatment pathway design, precision medicine and more. However, it’s important to remember that AI does have limitations which everyone should consider before implementing the technology into their business.
One of the challenges organizations face is ensuring the data sources that inform the AI feedback loops are accurate and large enough to develop the correct outputs. When considering AI technology, business leaders should make sure they ask the right questions before implementing it in their products or businesses.”
5. Rana Gujral, CEO at Behavioral Signals
“AI is in its infancy when it comes to healthcare. In 50 years we will remember this period as the stone-age of medicine when it comes to AI and health. Clinical medicine up to primary and secondary patient care involves thousands of processes that can actually be supported by AI and we're just starting with the ‘easy'. That usually involves procedures that are not invasive and human lives do not directly depend on the outcome. We can see applications of AI through virtual assistants, both for patient care and as medical staff assistants as well as smart wearables and social robots that are helping patients monitor their health and their emotions while collecting a lot of data. Robots in surgeries and AI software analyzing medical images for diagnosis are emerging.
While the scope of AI applications is limited today, there is a lot happening with researchers, investors, and companies. For example, how AI is being used to go through terabytes of genetic data to find gene correlations for rare diseases; something that would be impossible in a human lifetime, especially given the limited data, but now that specific projects are making it possible, more and more data are being contributed from all over the world. The immense potential of AI in healthcare is improved costs, service quality, and accessibility.”
6. Susan Wood, CEO of VIDA
“The market has come a long way in the past couple of years. 2017 was a year of hype, with a lot of uncertainty about what AI is and what it will mean for providers. There was fear related to job security and more questions than answers with regards to use-cases, workflow, and so on. In 2018, much of the fear and questions were resolved as use-cases became better defined and as workflow integration was addressed. Providers started to see AI as an essential way to assist or augment their work, and not as a threat. Now, in 2019, interest from providers has turned to action as many are developing an AI adoption plan, which includes a deeper investigation of the technologies, product evaluations, and budgeting for purchase.”
7. AJ Abdallat, CEO of Beyond Limits
“Artificial Intelligence will play a major role in the physician’s toolkit in the coming years. But, for AI to truly make a difference in healthcare it must go beyond conventional AI to unlock human potential and transform business. For example, at Beyond Limits we bring a highly sophisticated approach to solving healthcare problems, combining conventional numerical AI techniques with advanced symbolic reasoning to provide human-like insights. We reduce risk, provide explainable solutions, and bring insights powered by human expertise and advanced AI.”
8. Antony Edwards, COO of Eggplant
“The big AI news in healthcare is all around diagnostics (i.e., gathering patient test data and providing possible diagnoses that are then reviewed by a specialist). Healthcare was one of the use-cases that IBM targeted with their pioneering Watson technology.
The uptake on diagnosis has been slow; however, due to the very understandable concern of handing over this crucial activity to machines. Also, the fact that AI technology has moved so fast that Watson is now considered somewhat out-of-date.
AI has probably had more impact in the context of robotic process
automation (RPA). It automates standard administrative procedures such as patient check-in thus freeing up medical staff to spend more time on patient care.”
9. Russell Glass, CEO, Ginger
“There is significant potential for AI to transform the healthcare industry by lowering costs and improving access to and the quality of care. We’re still in the early days of figuring out how best to deploy AI within healthcare organizations, but it’s increasingly playing a role in improving patient care and empowering clinicians with data to make more informed diagnoses and develop personalized care plans. AI applications in healthcare will only continue to grow over the next couple of years. As a recent Intel survey shows, 54% of healthcare experts believe that we’ll be seeing widespread AI adoption over the next 5 years.”
10. Kabir Mahajan, Chief Strategy Officer at QUIBIM
“The healthcare industry is on the verge of a major transformation. Better, faster and cheaper (cost-effective) services are in demand not just by patients, but also by regional healthcare systems, hospitals, and clinics. There has been a huge advancement in technology development- from faster and more accurate diagnosis, to personalized treatments. AI is also being used for patient risk identification by healthcare systems (for readmissions risks, risk of cardiovascular disease), for drug discovery to identify new therapies from large databases thereby improving the success rate of drug development, for primary care by giving initial advice to patients in regions with limited or no access to doctors.
AI in healthcare has generated a huge buzz globally given that in Q2 2019, AI Healthcare start-ups raised a total of $ 864 Million through 75 deals! Regulatory agencies are also becoming more open to these technologies given that FDA has approved approximately 40 AI algorithms in Medicine in Radiology, Cardiology, Oncology, Endocrinology amongst other specialties.”
11. Keith Figlioli, General Partner at LRVHealth
“It is still very early but many parties including large tech are putting significant dollars into the AI / ML space. One of the largest VC funded areas over first half of the year has been AI / ML healthcare startups. Across all industries, I also believe that AI / ML healthcare startups accounted for the highest number of VC deals in the first half of the year.”
12. Allon Bloch, co-founder and CEO of K Health
“There is no question that AI has begun to transform the healthcare industry, but we’re still in the initial stages of defining the role AI will play when it comes to our health. The technology is being used in a variety of ways, including imaging and diagnostics, but the strongest potential for AI is in primary care. No one is patient zero, and collective health data from people around the world can give each person powerful insight into managing their own health.”
13. Charles Aunger, Managing Director at Health2047
“The healthcare system is in the midst of a tectonic, much-needed transformation. The secure transport of health data is central to improving U.S. healthcare and provides a unique opportunity to leverage leading-edge technology principles to create a trusted network. Even before the rise of digital health, it was a challenge for industry professionals to manage copious amounts of patient data.
These tasks have become harder as new data-driven technologies—like apps and wearables—are introduced and security threats are increasingly crippling to healthcare. Healthcare needs AI automation, blockchain technology, and semantic interoperability to protect patients against data security issues and grant them easy access to their medical records.”
14. Chris Bouton, founder & CEO of Vyasa Analytics
“What we’re all really talking about when we mention AI nowadays is, in fact, a new form of machine learning algorithms called “deep learning” algorithms. In fact, there’s a joke about AI which is, “If it’s written in Powerpoint, it’s AI. If it’s written in Python, it’s deep learning.” Right now, we’re still in the state in the healthcare industry of identifying the true benefits and capabilities of deep learning algorithms. While these algorithms absolutely have game-changing capabilities, the industry is just starting to identify the value of these approaches.”
15. Maxim Ivanov, CEO and co-founder of Aimprosoft
“Some development can be seen in improving diagnostics based on medical image analysis. Another prevailing area of interest is automated operational efficiency, which includes patient admittance and discharge, staff scheduling, financial collections, and other administrative issues. I would also pay attention to the steady growth of AI-empowered products for patients' wellbeing and a healthier lifestyle like exercise encouragement or reminders for taking medication. Predictive analytics and health trackers are the focus point where hospitals are ready to invest because it helps prevent patients' emergencies before they even occur. Such US hospitals as Cleveland Clinic, Johns Hopkins Hospital, Mayo Clinic have already taken steps towards predictive analytics development and usage.
Despite many opportunities AI can bring to the industry, there is a major stagnancy in AI application, be it a private or state healthcare sector. There are many hindering causes why its implementation is delayed. Many healthcare enterprises still use legacy software being unprepared for the change.”
16. Jennifer Hill, Chief Operating Officer at Remedy Analytics
“AI is being used in a variety of different ways spanning across the healthcare industry. A few of the most notable uses are utilizing true machine learning to aid and accelerate drug development, supporting frontline healthcare including medical imaging, hospital treatments, reduction of medical errors and patient profiles, and recognizing natural language to efficiently decipher patient records in a timely and cogent manner. Given the thousands of disparate systems used in healthcare today, the industry is focused on figuring out innovative ways to reduce administrative time, and make information clearer to patients, providers and administrators. Ultimately, mining the captured data provides guidance to R&D to make further strides in the improvement and provision of care.”
17. Dekel Gelbman, CEO of FDNA
“I believe we are in the stage of early growth. There is a lot of promise in virtually every domain in healthcare, but there is still a lot of hype as well. Most solutions are not real AI and most AI-based solutions are not really adopted in clinical settings yet. However, AI is getting a lot of attention and recently, a lot of focus on validation, which is very important for adoption in healthcare. I think that we are entering an interesting decade for AI in healthcare, in which we will see a lot of growth and learning, both for developers and for users, as well as for policy makers.”
18. Emi Gal, co-founder and CEO of Ezra
“AIs with intelligence comparable to that of experienced radiologists are being built left and right. For example, a team at Duke built an AI algorithm able to make biopsy recommendations with expertise similar to that of a seasoned radiologist based off of ultrasound images of thyroids. Similar neural networks are being built for different organs; it’s incredible.”
19. Niven Narain, Co-Founder, President & CEO of BERG
“First off, it is absolutely essential to separate the hype from the reality regarding the use of AI in transforming the healthcare industry. The challenge is that what statisticians were doing 10-20 years ago, is now being branded as AI. Unfortunately, that is not AI.
Artificial Intelligence goes beyond machine learning and should create de novo and prescriptive insight from data to guide decision making. AI is changing how we diagnose patients by looking at imaging, CT, and PET scans, identifying patterns in patients’ behavior, developing improved pharmaceuticals docking into the target, incorporating patients medical and demographic information, selecting patients based on their genetic or molecular profile, as well as use in insurance for claims data. In reality, AI and advanced analytics are being used for almost everything, but again is it AI or just advanced analytics?”
20. Sean Lane, CEO of Olive
“Category interest is growing, with more than half of hospital leaders planning to invest in AI by 2021. According to a recent Sage Research survey commissioned by Olive, improving efficiency is a top strategic priority, and leaders are increasingly turning to AI to help them achieve their goals. We have found that hospital leaders are seeking a vendor that can deliver a holistic solution that delivers a fast path to ROI – a partner who will build, deliver, monitor and support their technology.”
21. Dr. Anuj Shah MD, founder of Apex Heart and Vascular Care
“Artificial Intelligence is slowly becoming more commonplace in the healthcare industry. As technology improves, tasks once thought to always require human decision making are being accomplished more accurately with machine learning. For example, a radiology program developed at Stanford was able to correctly identify pneumonia more often than a human radiologist. Several large companies including Microsoft, Google, and Intel are heavily investing in the development of artificial intelligence for healthcare use.”
22. Patrick Gauthier, Director of Healthcare Solutions at Advocates for Human Potential
“Hard to pin down. It has been used to motor predictive analytics (PA) for quite a while. Predictive analytics is what powers actuarial studies, ratings, and risk-setting in insurance. Today, PA is being used to identify how people in groupings of chronic conditions are likely to follow a course of treatment along a continuum of care and to help providers steer these folks in that direction. Similarly, AI powers clinical decision support systems in that they aggregate diagnostic indices and support patient placement at a particular level of care. These are both examples of managed care strategies.”
23. Neal Liu, Co-Founder and CTO of uCare.ai
“The healthcare industry in Asia is still in its early stages. While some businesses have been able to successfully implement AI solutions, others are still in the process of understanding and learning about the technology. Many companies are spending a lot of time, resources and money on organizing, cleaning and warehousing their data. However, this is not required to use our solution – we work with our client's dirty data and do not require a data lake, any additional infra investment or dashboard/app for clients to benefit from our solutions.”
24. Sanket Shah, Clinical Assistant Professor at the University of Illinois at Chicago's Masters of Science in Health Informatics and Health Information Management
“I would say it is still in its infancy stages, but progressing and evolving. There is a tremendous amount of initiative and investment into AI within healthcare, however, most organizations are only focusing on a handful of use cases right now. I suppose it is a “bite off more than one can chew” mindset when it comes to AI application. We’re starting to see some results and fine-tuning when it comes to AI and as more information becomes available the stronger the offerings become. The reality is that AI is certainly not a core competency from a broad industry perspective. There are non-traditional healthcare players (Alphabet, Microsoft, and others) that are driving AI offerings to become more accessible from both a provider and patient perspective. However, most organizations are still reluctant when it comes to trying to take full advantage of AI whether that be operational automation, clinical application, and/or consumer experience.”
25. Kevin Harris, CEO of CureMetrix
“Artificial intelligence (AI) in healthcare has evolved quickly, and today interest is surging. After its early days in R&D and testing, we’re now seeing the emergence of powerful FDA-cleared products with vast potential to reshape and enhance patient diagnosis and treatment. At the same time, AI awareness and acceptance is broadening across the industry. There’s a genuine interest and recognition of its potential to improve clinical and financial outcomes.”
26. Shantanu Nigam, CEO of Jvion
“The healthcare industry is moving from a mindset of innovators to the early majority in the adoption curve. We have proof points of where AI works, where it doesn’t, and the impact that the right AI can have on a patient population. But the industry is still young. There is widespread skepticism on the impact that AI can have on patient outcomes. And there are false narratives that are promulgated, which act as a barrier to adoption. Clinicians are overburdened and alarm fatigued. AI that adds to alarm fatigue without providing actionable insights simply does not work. What we know is that the AI that works for healthcare is pointing clinicians to the patients, the adverse events, and actionable interventions where they can have the greatest impact. AI holds the keys to alleviating that overload and making sense of the expanding universe of patient data.”
27. Nagi Prabhu, Chief Product Officer at Solutionreach
“AI is a big buzzword that’s very misunderstood. Adoption of AI is not an end state but rather part of a data intelligence continuum with limitless potential. The industry is at the infancy of adopting AI. The first few steps of the continuum start with data science/machine learning/natural language processing (NLP), then transition to AI. AI enables systems to act based on patterns recognized through machine learning. We need to purposefully mature from machine learning to AI, then from AI to deep learning/self-learning — and to whatever comes next.”
28. Rajat Sharma, founder and CEO at Cover2Protect
“AI has been there for a long time in different shapes and forms but today the power of AI is unleashing primarily because of adoption of APIs and open architecture because of which numerous amount of data pipes are getting opened up. The tremendous volume of data produced by the growing presence of sensors and computers that produce, capture, distribute, and store data. This ‘Big Data’ is especially prevalent in healthcare: Hospitals are now producing 50 Petabytes of data per year,3 coming from the variety of SaaS products, EMRs, medical devices, wearables, and medical images.”
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