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In 2011, IBM’s Watson became a sensation after its Jeopardy debut, being able to process natural language and scan its library of information to retrieve the correct information in a matter of seconds. About two years later, Watson was deployed to its first business application, and what seemed like a natural fit, healthcare. With the progression of virtual doctor visits, healthcare apps, and online patient records, it seemed like Watson could be the jumpstart to an entirely transformed healthcare industry.

IBM Watson Health was invented to solve the globes most pressing health challenges by processing trillions of data points and evaluating through analytics and AI. It combines human expert knowledge with augmented intelligence (AI), to help healthcare workers and researchers around the world use data and knowledge to provide insights, which make vastly more informed decisions about patient care throughout hospitals and health organizations. Watson’s memory banks hold knowledge of every illness, disease, and recorded study and its computer based processing doesn’t fall susceptible to the kind of cognitive bias that can throw off doctors. It could provide a  breakthrough in just a couple of seconds. IBM hoped that if Watson could bring instant and vast expertise to hospitals and healthcare organizations and education centers all around the world, it seemed possible that the technology actually could reduce diagnosis errors, optimize treatments, and even alleviate staffing shortages. This is not to say Watson is a replacement, but helping doctors and clinicians respond to their jobs faster and better.

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A few years after initial deployment, Watson’s helpfulness was hard to quantify. With billions of dollars invested into the artificial intelligence, Watson hasn’t revolutionized medicine like many people had hoped. Still, Watson did have very significant achievements. It developed a treatment plan for a cancer patient in less than 10 minutes, in comparison to the typical 160 hours of human experts. And as a research tool, Watson analyzed over 70,000 studies to find six other alternatives to modifying a protein used to prevent tumor growth, where a normal researcher can only read just 300 studies per year.

Currently, IBM is still making investments into Watson. There is a significant shift in marketing, now branding Watson as another tool at doctors and researchers’ disposal to confirm, narrow, or hypothesize, rather than a one stop solution. Additionally, the expansion of all industries in cloud storage and cloud computing has refocused attention back on Watson and how AI will contribute to a growing tech infusion into multiple industries. This is not to say that Watson is out of the dark, as the division of IBM continues to lay off engineers as the difficulties of turning AI into a profitable business continue.

Still, IBM had made several strategic acquisitions in an attempt to bolster Watson’s market readiness. Three companies were bought by IBM for the vast quantities of data each possessed in addition to the proprietary data analytics systems that processed the data. Secondarily, IBM captured the customers that these companies were using, mainly healthcare providers who saw the benefit of health analytics to improve care and business.

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IBM’s website notes that “…we also recognize that progress requires partnership. We provide access to a connected ecosystem of health experts, data, and partners to support digital transformation.” Which could be interpreted as pitch language for “the product doesn’t really work quite yet”. It does provide some benefit, but there are a lot of kinks to work out before it is the dream invention IBM set out to build. There is a high certainty, that IBM will look for a strategic partner who can provide either better technology that can help connect the missing pieces from Watson to the current healthcare landscape or a strategic partner that has a large volume of healthcare data, according to several employees and media outlets.

Ideally, IBM sells off the Watson division to another company in the coming years. After more than $15 billion in investment, shareholders are getting anxious about the future of Watson health and a sale could help rein the company’s free cash flow back in. Last month the Wall Street Journal reported that IBM is studying a potential sale to a private-equity firm or industry player. Watson was a large bet on the future for IBM, but the disappointment of the project could be salvaged with a strong sale of the technology and healthcare data. Sales have been down in many quarters throughout the last decade since Watson’s launch.

Looking beyond a sale or reinvestment, even today’s best augmented intelligence fails to provide a clear and user friendly output of complex medical information. And as IBM has found out, encoding a human’s expertise into software in just as difficult as it sounds. This means it is no secret that IBM has learned from some painful losses in the marketplace. In the next five years we will see how IBM manages to find value in Watson and how it refines the mission that was originally cast to revolutionize medicine a decade ago. It either is purchased or needs substantial reform to be of use and finally turn a profit. In the next 5 years if IBM holds onto their investment, it will likely face increasing shareholder pressure to limit the technological ability of Watson and instead find practical, time saving uses for it.

Long-term, artificial and augmented intelligence is a given in medicine. It has great potential to reshape the entire industry, but I think we are going to be looking at a human first, Watson, second world. Perhaps Watson can be reconfigured as a confirmation tool but not as a tool to diagnose. As a confirmation tool, Watson could use the ability to read 250 times the amount of studies and journals human scientists can, and make sense of trillions of data points about patients. There is definitely value in a software that a doctor can input symptoms or genetic history and can predict future illness or disease, just as particular gene sequencing has led to the early detection of certain cancers, and perhaps with more patient information Watson can find its calling in detecting patterns of illness and disease and be an early detection tool. In the long-term, the vast amounts of data have unlimited potential, but for the humans that will interpret and read the outputs of Watson, it will come down to what is most beneficial and valuable for the industry.

Alternatively, Watson seems fully capable of helping insurers, pharmaceuticals, and hospitals manage and store their data in a way that is more efficient and valuable to consumers. In an ever increasingly global society, having medical records at the tap of your phone screen could be potentially lifesaving if an emergency happens outside of your primary physician’s care. One of the key changes to watch in the next 10 years is how, or if, medicine changes from treatment to prevention. That is to say doctor’s ability to focus on more preventive actions and keeping people healthy versus treating illness when they show symptoms.

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Doctors and medical professionals understanding and practice would still have the potential to be revolutionized in a sale or redevelopment of Watson. Just as IBM is looking to turn a profit on Watson, there is a need to streamline and modernize the way global medicine is accessed, performed, and utilized. “Doctors go to work every day—especially the people on the front lines, the primary care doctors—with the understanding that they cannot possibly know everything they need to know in order to practice the best, most efficient, most effective medicine possible,” says Herbert Chase, a professor of medicine and biomedical informatics at Columbia University who collaborated with IBM in its first health care efforts. “But Watson, he says, could keep up”— and if turned into a tool for “clinical decision support,” could allow doctors and other healthcare workers to stay current.

Under a refined Watson, patients may be able to use existing and new healthcare apps to input their medical history and data and be recommended doctors, frequency of necessary appointments, and retrieve important medical information quickly in an emergency. This could cut down on wait times to see a practitioner, shorten referral times to see a specialist, and help patients to more easily understand often complex diagnoses and treatment plans.

There is no doubt about the great potential for AI to reshape the healthcare landscape, but Watson is not likely going to be the only answer. Technology companies and projects either adapt at lightning speed or are beat out by competitors. Watson may go down as a first mover in the healthcare AI space, but it’s certainly not the only one as competitors can learn from Watson’s mistakes and get ahead. “IBM has great potential, but in modern business, you adapt or go away. Workers will go to other companies,” says an IBM engineer. “The winner will not be IBM.”

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[1] https://www.ibm.com/watson-health

[2]https://newsroom.ibm.com/2019-02-13-IBM-Watson-Health-and-the-Broad-Institute-Launch-Initiative-to-Help-Clinicians-Predict-the-Risk-of-Cardiovascular-Disease-with-Genomics-and-AI

[3]https://www.nytimes.com/2016/10/17/technology/ibm-is-counting-on-its-bet-on-watson-and-paying-big-money-for-it.html

[4]https://spectrum.ieee.org/the-human-os/artificial-intelligence/medical-ai/layoffs-at-watson-health-reveal-ibms-problem-with-ai

[5] https://www.wsj.com/articles/ibm-explores-sale-of-ibm-watson-health-11613696770

[6] https://www.livescience.com/50479-5-ibm-watson-facts.html

12 comments

  1. Great post! Last week I wrote about how the US Open Tennis tournament uses IBM Watson’s technology to predict the likelihood of a player winning a match. It is interesting to see how IBM Watson is used in other areas such as healthcare. I also agree that they might be falling behind by not fully capitalizing on the investment; however, I see human brains and AI working together to solve some of the most challenging problems in the future, such as detecting and curing some of the world’s most complex diseases.

  2. I think you hit the nail on the head when you said, “Perhaps Watson can be reconfigured as a confirmation tool but not as a tool to diagnose.” Can you imagine a life or death situation, perhaps a cancer diagnosis or Alzheimer’s disease diagnosis and a computer spits out the results. I think when we consider direct patient care, we need to take into consideration the ideas of compassion and empathy. Which I am truly not sure Watson can provide. While I do believe AI can be used in conjunction with humans, I certainly don’t ever see it replacing human care.

  3. Thank you for the great insight into digital technology in the health care industry. With digital tools like Watson, doctors and nurses can quickly identify and confirm diseases and illnesses to find solutions faster than they do today. Also, as I was reading through your blog, I wondered what is holding IBM back from truly realizing the potential Watson can bring to help the health care industry and its bottom line. Furthermore, in the final paragraph, you answered this question from a broad viewpoint in that IBM needs to adapt and modernize its business model, or they will be left behind. Both of my parents work for IBM, and I know anecdotally about the company’s struggles to keep up with their competitors. Finally, I support a recommendation you made earlier in your post about IBM selling Watson to another firm with the technical expertise to maximize the benefits it will bring to society.

  4. I think this is great medical advance for Doctors. On another note, a lot of people will google their symptoms before they go to the doctors. Often times this leads to mis-judgement based on medically inaccurate information. By the time they get to a doctor it could be too late. A few months ago in another MBA class the CEO/Founder of a Boston based company came into class, Buoy. The company uses AI to cross reference a database of medical papers/journals to recommend a plan of action/potential diagnosis of symptoms. Maybe Watson and this technology together could make the medical field a lot more “smarter.” https://www.buoyhealth.com/company

  5. I’m skeptical of implementing something like Watson on a broader scale, but this does bring to mind something I believe to be expanding in the years to come: telemedicine. A biproduct of the pandemic that’s here to stay, telemedicine is viable in so many cases and in theory should free up doctors.

  6. Very informative and insightful! With regards to AI, I think the tendency has been to envision a future where machines flat out replace humans but – as you demonstrate in the blog – it will likely remain a “collaborative” effort between human and AI in order for us to maximize the benefit of these tools. It’s interesting to follow the trajectory of Watson as you have outlined it in the post, and to realize that it is still very much a work in progress that is continuing to evolve as the landscape shifts, and the realization sharpens that the intended outcome is not quite realizable. I think it’s also a good reminder that often times a lot of new technologies and innovations may set out for one purpose and wind up being utilized in a completely different capacity or realize different benefits.

  7. Great article! IBM is changing the world. Their Watson project will have a tremendous effect if appropriately applied to the medical world in particular. I don’t see why a doctor would be skeptical about using Watson as another resource to check his hypothesis or diagnostic. Why say no to the best tools and resources?

  8. Your jeopardy picture was the last time I’ve thought about Watson. I remember, as you noted, how Watson was going to change our day-to-day lives and the way we worked. Jeopardy was the platform IBM used to convince us that we were seeing the future. When in reality, it was more of a marketing gimmick.

    I didn’t realize that Watson did have success in the medical field. I love hearing that its data computation capabilities have been used to treat diseases and help medical professionals.

    On the other hand, I am not surprised to hear that IBM is considering selling Watson. IBM has been a struggling company this decade and has failed to adapt to our new digital world. After reading your post I realize that Watson is a perfect symbol of this. Continuing to invest billions of dollars into a technology that has not shown any ROI and that hasn’t lived up to its original promise. I hope IBM sells and another company can give Watson a chance to thrive in a 21st century digital world.

  9. Well-written article on a very cool topic. Makes me wonder, though, what happens if Watson is wrong? Is IBM taking on the liability of a doctor relying on this technology? Definitely not, but should they be? While Westlaw created something that reads your briefs and gives you tips on what to include or does the same for opposing counsel, it seems different since (1) humans are involved at least in the drafting stage and (2) human lives aren’t at risk.

  10. Yes, I think IBM was certainly right to double down on Watson those many years ago, but they just seem to have not been able to execute on it well enough. My money is on Google for the long-term success at AI. They just have more experience working with data, which I think is key in this space.

  11. I would be curious to see how this tool could expand access to healthcare for people who are not insured or underinsured, given that while it may be a joint tool, it might reduce the time a physician needs to be managing the patient’s care. This could be an additional resource for communities that experience disparities in access to health insurance for common, low stakes doctor’s visits (sniffles, ear infections, other common test-centric illnesses).

    I agree with some of the previous comments that have caution regarding an exclusive use of AI for diagnostics, especially for people with more complex medical histories, but think that the expansion of healthcare access could be crucial for ensuring that all individuals have access to a physician if they are not feeling well.

  12. Cool post! I’m really interested to see how the healthcare industry will incorporate these technological advancements within their practice since there has been a shift to Telehealth post pandemic. I think perhaps using AI technology along with wearables for diagnostic purposes might help yield “more accurate and personalized” results. AI alone can only do so much.

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