Will More Big Data Make AI Deliver Results

April 6, 2020

Many companies have issued news releases about their coronavirus research support. Personally I find the majority of these “real news” announcements low ball marketing at its finest. The coronavirus problem is indeed serious, and researchers, art history majors, and MBA executives who hop on the “We are helping” bandwagon are amusing.

I read a 3,500 ZDNet article titled:

AI Runs Smack Up Against a Big Data Problem in COVID-19 Diagnosis. Researchers around the world have quickly pulled together combinations of neural networks that show real promise in diagnosing COVID-19 from chest X-rays and CT scans. But a lack of data is hampering the ability of many efforts to move forward. Some kind of global data sharing may be the answer.

Now that’s an SEO inspired title, but the write up makes one amazing assertion: More data will allow medical AI systems to output actionable information.

If I run through the litany of medical AI revolutions, my fingers would get tired clicking and mousing. The IBM Watson silliness is a good example, and it encapsulates the problem of using collections of numerical recipes to help physicians deal with cancer. Google has not made much, if any, progress on solving death. Remember that “hard problem.” Pushing deeper into the past there was NuTech Solutions’ ability to identify individuals likely to get diabetes based on sparse data and ant algorithms.

How did these companies’ efforts work out?

Failures from my point of view.

The write up runs down a number of research efforts. Companies like DarwinAI are mentioned. There are quotes which provide guidance to organizations challenged to find the snack room; for example:

“I think it would help if the WHO made a central database with de-identifying mechanisms, and some really good encryption,” said Dr. Luccioni. “That way, local health authorities would be reassured and motivated to share their data with each other.”

The problem is that smart software is mostly implementation of methods known in some cases for hundreds of years. These smart systems use recursion, feedback loops, and statistical procedures to output statistically valid (probable) information.

How are these systems working? There are data, but they are conflicting, disorganized, and inconsistent. News flash. That’s how information is. There is zero evidence that more data can be verified, normalized, processed in near real time to allow smart software to demonstrate it can do more than generate marketing collateral.

The companies pitching their artificial intelligence should articulate the reality of the outputs their workflows of algorithms can actually generate.

That might help more than the craziness of wanting data to be better, having some magic wand to normalize the messy real world of information, and converting what are mostly graduate school projects into something useful beyond speeding up some lab tests and getting a “real” job.

Will this happen? Not for a long time. Data are not the problem. Humans are the problem because the idea of creating a consistent, verified repository of on point data has not been achieved for small domains of content. Forget global data.

Don’t believe me. Check out any online system. Run some queries. Is “everything” in that system or federated system? What about a small collection of data; for example, the data on your mobile? What’s there that you can access? “What?” you ask. Yeah, the high value data are sucked away and those data are not shared with “everyone” including you who created the data in the first place.

Smart software performs some useful functions. Will data make Bayesian methods or patented techniques like those from Qure.ai “solve” Covid?

Hard in reality. Easy in ZDNet articles. Even easier for marketers. And the patients suffering? What? Who? Where?


Stephen E Arnold, April 5, 2020

Health Care: Data an Issue

June 28, 2018

Healthcare analytics is helping doctors and patients make decisions in ways we never could have dreamed. From helping keep your heart healthy to deciding when to have major surgery, analytic numbers make a big impact. However, that data needs to be perfect in order to work, according a recent ZD Net story, “Google AI is Very Good at Predicting When a Patient is Going to Die.”

According to the story:

“As noted, 80 percent of the effort in creating an analytic model is in cleaning the data, so it could provide a way to scale up predictive models, assuming the data is available to mine…. “This technique would allow clinicians to check whether a prediction is based on credible facts and address concerns about so-called ‘black-box’ methods that don’t explain why a prediction has been made.”

This really illustrates how powerful clean data can be in the health field. However, cleaning data is just about the most misunderstood wallflower in the often tedious world of machine learning and data science—not just in healthcare. According to Entrepreneur magazine, the act of filling in blanks, removing outliers, and basically looking at all the data to make sure it will be accurate, is the most important part of the process and also the hardest role to fill on a team.

Garbage in, garbage out. True decades ago. True today. How do we know? Just ask one of IBM Watson’s former health care specialists. Querying patients who were on the wrong end of a smart output may be helpful as well.

Patrick Roland, June 28, 2018

Google and AI Digital Shrooms

March 30, 2018

Magic mushrooms are a delightful way to experience reality as well as hurt your body and become addicted to drugs.  They were a big symbol of the 1960s-70s counterculture.  Beyond their hallucinogenic properties, medical experts discovered they have medicinal uses too.  Mushroom enthusiast loves the mold, but there might be a way for them to trip without breaking any laws.  The International Business Times reported that “Hallucination Machine Uses Google AI, Gives Magic Mushroom-Like ‘Trip’ Without Drugs.”

The possibilities of virtual reality have been imagined for years, but only now can we fully begin to explore the possibilities.  One way researchers are testing virtual reality is with the Hallucination Machine, built on Google AI and uses a virtual reality headset.   The Hallucination Machine allows users to “trip” without the drugs’ harmful effects. Scientists are fascinated with hallucinations and hallucinogens because they love to study the brain’s processes when it “trips out.”

Sussex University’s Sackler Centre for Consciousness Science published a paper in the Scientific Reports journal discussing how the Hallucination Machine compares to real drug-induced hallucinations.

Hallucinations help scientists focus their study on areas of the brain that are affected when there is an altered reality. Using hallucinogens alters the chemical composition of the brain, which makes it hard to isolate just the visual effects. So the team used Google’s DeepDream system, which uses a neural network approach to try and identify patterns and features in images. You can actually try it out for yourself online.  DeepDream works by creating patterns and over emphasizing on certain recurring details that helps put our brain into perception overdrive, so much so that it starts to imagine stuff that isn’t actually there.

The Sackler Center conducted two tests.  The first exposed participants to DeepDream and users experienced hallucinations similar to those caused by magic mushrooms.  The second tested participants’ time perception, but the Hallucination Machine cannot recreate that psychedelic experience yet.

Replicating the magic mushroom’s tripping experience is still in the development phases, but give it a few more years and this will probably be a popular virtual reality program.

Whitney Grace, March 30, 2018

AI Makes Life-Saving Medical Advances

January 2, 2018

Too often we discuss the grey area around AI and machine learning. While that is incredibly important during this time, it is also not all this amazing technology can do. Saving lives, for instance. We learned a little more on that front from a recent Digital Journal story, “Algorithm Repairs Corrupted Digital Images.”

According to the story:

University of Maryland researchers have devised a technique exploits the power of artificial neural networks to tackle multiple types of flaws and degradations in a single image in one go.

The researchers achieved image correction through the use of a new algorithm. The algorithm operates artificial neural networks simultaneously, so that the networks apply a range of different fixes to corrupted digital images. The algorithm was tested on thousands of damage digital images, some with severe degradations. The algorithm was able to repair the damage and return each image to its original state.

The application of such technology crosses the business and consumer divide, taking in everything from everyday camera snapshots to lifesaving medical scans. The types of faults digital images can develop include blurriness, grainy noise, missing pixels and color corruption.

Very promising from a commercial and medical standpoint. Especially, the medical side. This news, coupled with the story in Forbes about AI disrupting healthcare norms in 2018 makes for a big promise. We are looking forward to seeing what the new year brings for medical AI.

Patrick Roland, January 2, 2018

Watson and CDC Research Blockchain

December 29, 2017

Oh, Watson!  What will IBM have you do next?  Apparently, you will team up with the Centers for Disease Control and Prevention to research blockchain benefits.  The details about Watson’s newest career are detailed in Fast Company’s article, “IBM Watson Health Team With the CDC To Research Blockchain.”  Teaming up with the CDC is an extension of the work IBM Watson is already doing with the Food and Drug Administration by exploring owned-mediated data exchange with blockchain.

IBM chief science officer Shahram Ebadollahi explained that the research with the CDC and FDA with lead to blockchain adoption at the federal government level.  By using blockchain, the CDC hopes to discover new ways to use data and expedite federal reactions to health threats.

Blockchain is a very new technology developed to handle sensitive data and cryptocurrency transactions.  It is used for applications that require high levels of security.  Ebadollahi said:

 ‘Blockchain is very useful when there are so many actors in the system,’ Ebadollahi said. ‘It enables the ecosystem of data in healthcare to have more fluidity, and AI allows us to extract insights from the data. Everybody talks about Big Data in healthcare but I think the more important thing is Long Data.’

One possible result is that consumers will purchase a personal health care system like a home security system.  Blockchain could potentially offer a new level of security that everyone from patients to physicians is comfortable with.

Blockchain is basically big data, except it is a more specific data type.  The applications are the same and it will revolutionize the world just like big data.

Whitney Grace, December 29, 2017

Humans Living Longer but Life Quality Suffers

December 28, 2017

Here is an article that offers some thoughts worth pondering.  The Daily Herald published, “Study: Americans Are Retiring Later, Dying Sooner And Sicker In Between”.  It takes a look at how Americans are forced to retire at later ages than their parents because the retirement age keeps getting pushed up.  Since retirement is being put off, it allows people to ideally store away more finances for their eventual retirement.  The problem, however, is that retirees are not able to enjoy themselves in their golden years, instead, they are forced to continue working in some capacity or deal with health problems.

Despite being one of the world’s richest countries and having some of the best healthcare, Americans’ health has deteriorated in the past decade.  Here are some neighbors to make you cringe:

University of Michigan economists HwaJung Choi and Robert Schoeni used survey data to compare middle-age Americans’ health. A key measure is whether people have trouble with an “activity of daily living,” or ADL, such as walking across a room, dressing and bathing themselves, eating, or getting in or out of bed. The study showed the number of middle-age Americans with ADL limitations has jumped: 12.5 percent of Americans at the current retirement age of 66 had an ADL limitation in their late 50s, up from 8.8 percent for people with a retirement age of 65.

Also, Americans’ brains are rotting with an 11 percent increase in dementia and other cognitive declines in people from 58-60 years old.  Researchers are not quite sure what is causing the decline in health, but they, of course, have a lot of speculation.  These include alcohol abuse, suicide, drug overdoses, and, the current favorite, increased obesity.

The real answer is multiple factors, such as genes, lifestyle, stress, environment, and diet.  All of these things come into play.  Despite poor health quality, we can count on more medical technological advances in the future.  The aging population maybe the test grounds and improve the golden years of their grandchildren.

Whitney Grace, December 28, 2017

Silicon Valley Has the Secret to Eternal Life

December 27, 2017

Walt Disney envisioned his namesake park, Walt Disney World, to be a blueprint for the city of the future.  Disney was a keen futurist and was interested in new technology that could improve his studios and theme parks.  His futuristic tendencies led to the urban legend that he was cryogenically frozen and will one day be revived.  Disney wasn’t put on the ice, but his futuristic visions are carried out by Silicon Valley technologists seeking immortality.  Quartz reports on the key to eternal life in the article, “Seeking Eternal Life, Silicon Valley Is Solving For Death.”

Death is the ultimate problem that has yet to be solved.  Many in Silicon Valley, including Oracle’s Larry Ellison, are searching for a solution to prolong life with anti-aging research.  Bill Maris convinced Alphabet’s Larry Page and Sergey Brin to start Calico, Google’s billion-dollar effort to cure aging.  Also, cryogenics remains popular:

Other denizens of the valley pursue cryogenics or cryonics, which is the process of freezing oneself in a vat of liquid nitrogen soon after death. They do this in the hope that it will suspend them in time, preserving them for a future when science can bring them back to life. There are about 350 people already frozen worldwide with another 2,000 signed up—but yet to die.

Medical breakthroughs have already extended the US lifespan and that of other developed nations.  Developing nations still have short lifespans and it draws the conclusion that wealthier people will live forever, while the poor ie quicker.  It is questionable that the extra years tacked onto people’s lives are really worth it because many people spend them unable to care for themselves or in pain.

The article spins into current anti-aging research, then into philosophy about humans vs. machines and what makes a person a person.  Throw in some science-fiction and that is the article in short.

Whitney Grace, December 27, 2017

Search System from UAEU Simplifies Life Science Research

December 21, 2017

Help is on hand for scientific researchers tired of being bogged down in databases in the form of a new platform called Biocarian. The Middle East’s ITP.net reports, “UAEU Develops New Search Engine for Life Sciences.” Semantic search is the key to the more efficient and user-friendly process. Writer Mark Sutton reports:

The UAEU [United Arab Emirages University] team said that Biocarian was developed to address the problem of large and complex data bases for healthcare and life science, which can result in researchers spending more than a third of their time searching for data. The new search engine users Semantic Web technology, so that researchers can easily create targeted searches to find the data they need in a more efficient fashion. … It allows complex queries to be constructed and entered, and offers additional features such as the capacity to enter ‘facet values’ according to specific criteria. These allow users to explore collated information by applying a range of filters, helping them to find what they are looking for quicker.

Project lead Nazar Zaki expects that simplifying the search process will open up this data to many talented researchers (who don’t happen to also be computer-science experts), leading to significant advances in medicine and healthcare. See the article for on the Biocarian platform.

Cynthia Murrell, December 21, 2017

Watson Works with AMA, Cerner to Create Health Data Model

December 1, 2017

We see IBM Watson is doing the partner thing again, this time with the American Medical Association (AMA). I guess they were not satisfied with blockchain applications and the i2 line of business after all. Forbes reports, “AMA Partners With IBM Watson, Cerner on Health Data Model.” Contributor Bruce Japsen cites James Madera of the AMA when he reports that though the organization has been collecting a lot of valuable clinical data, it has not yet been able to make the most of it. Of the new project, we learn:

The AMA’s ‘Integrated Health Model Initiative’ is designed to create a ‘shared framework for organizing health data , emphasizing patient-centric information and refining data elements to those most predictive of achieving better outcomes.’ Those already involved in the effort include IBM, Cerner, Intermountain Healthcare, the American Heart Association, the American Academy of Family Physicians and the American Medical Informatics Association. The initiative is open to all healthcare and information stakeholders and there are no licensing fees for participants or potential users of what is eventually created. Madara described the AMA’s role as being like that of Switzerland: working to tell companies like Cerner and IBM what data elements are important and encouraging best practices, particularly when patient care and clinical information is involved. The AMA, for example, would provide ‘clinical validation review to make sure there is an evidence base under it because we don’t want junk,’ Madara said.

IBM and Cerner each have their own healthcare platforms, of course, but each is happy to work with the AMA. Japsen notes that as the healthcare industry shifts from the fee-for-service approach to value-based pricing models, accurate and complete information become more crucial than ever.

Cynthia Murrell, December 1, 2017

Consumer Health Search: An Angle for an Amazon Black Friday Sale?

November 24, 2017

I read “How Consumers Search for Health Care.” What struck me as interesting about this article’s information was that the data reminded me of research conducted i 1986 by the one time commercial online giant Information Access, a unit of Ziff Communications. We developed the Health Reference Center, which was an innovative service at that time. A kiosk allowed a user to obtain curated information about a medical condition. I recall we placed these Health Reference Centers in libraries and a handful of forward thinking health care facilities. We did tons of research, and the product included a number of interesting features.

I matched the findings reported in the article with my recollection of some of the research we conducted as part of the IAC product development process. One finding which was decidedly different was the preference for millennials for convenience. If the data in the article are accurate, 40 percent of the millennials in the sample like convenience which translates to mobile usage and online scheduling.

Other data points were in line with the findings from three decades ago; for example, ease of use and finding solutions that would be covered by insurance companies.

What do these data suggest? Health care is unlikely to be able to deal with expectations for mobile scheduling and patient convenience. As for shopping around for a deal on a treatment or procedure, Amazon, not established health care providers, may be encouraged to enter the field.

Black Friday deals on nose jobs and hip replacements may sound interesting to the Bezos behemoth. Use an Amazon credit card? One might get some Amazon credits which might be applied to the next procedure. Prime cut?

Stephen E Arnold, November 24, 2017

Next Page »

  • Archives

  • Recent Posts

  • Meta