Tag: Healthcare

Mobile health (mHealth) takes off in Kenya

Posted on by Ray in Cloud services, Distributed computing, Information economy, Market dynamics, Strategic Inflection Points, Systems, Visionary leadershp
iHanging out with Kenya Techies by whiteafrican (cc) (from Flickr)
Hanging out with Kenya Techies by whiteafrican (cc) (from Flickr)

Read an article today about startups and others in Kenya  providing electronic medical care via mHealth and improving the country’s health care system (see Kenya’s Startup Boom).

It seems that four interns were able to create a smartphone and web App in a little over 6 months, to help track Kenya’s infectious disease activity.   They didn’t call it healthcare-as-a-service nor was there any mention of the cloud in the story, but they were doing it all, just the same.

Old story, new ending

The Kenyan government was in the process of contracting out the design and deployment of a new service that would track the cases of infectious disease throughout the country to enable better strategies to counteract them.  They were just about ready to sign a $1.9M contract with one mobile phone company when they decided it was inappropriate for them to lock-in a single service provider.

So they decided to try a different approach, they contacted the head of the Clinton Health Access Initiative (CHAI) who contacted an instructor at Strathmore University who identified four recent graduates and set them to work as interns for $150/month. They spent the spring and summer gathering requirements and pounding out the App(s).  At the end of the summer it was up and running on smart phones and the web throughout their country.

They are now working on an SMS version of the system to allow others who do not own smart phones to be able to use the system to record infectious disease activity. They are also taking on a completely new task to try and track government drug shipments to hospitals and clinics to eliminate shortages and waste.

mHealth, the future of healthcare

The story cited above says that there are at least 45 mHealth programs actively being developed or already completed in Kenya. Many of them created by a startup incubator called iHub.  We have written about Kenya’s use of mobile phones to support novel services before (see Is cloud a leapfrog technology).

Some of these mHealth projects include:

  • AMPATH which uses OpenMRS (open sourced medical records platform) and SMS messaging to remind HIV patients to take their medicines and provides call-in for questions about the medication or treatments,
  • Daktari, a mobile service provider’s call-a-doc service that provides a phone-in hot-line for medical questions, in a country with only one doctor per every 6000 citizens, such phone-in health care can more effectively leverage the meagre healthcare resources available,
  • MedAfrica App which provides doctors or dentists phone numbers and menus to find basic healthcare and diagnostic information in Kenya.

There are many others mHealth projects on the drawing board including a national electronic medical records (EMR) service, medical health payment cards loaded up using mobile payments, and others.

Electronic medical care through mHealth

It seems that Kenya is becoming a leading edge provider of mHealth solutions based in the cloud mainly because it’s inexpensive, fits well with technology that pervades the country, and can be scaled up rapidly to cover its citizens.

If Kenya can move to deploy healthcare-as-a-service using mobile phones, so can the rest of the third world.

Speaking of mHealth, I got a new free app on my iPhone the other day called iTriage, check it out.

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Analog neural simulation or digital neuromorphic computing vs. AI

Posted on by Ray in Artificial Intelligence, Cognitive computing, IBM SyNAPSE chip, IBM Watson, MIT analog brain chip
DSC_9051 by Greg Gorman (cc) (from Flickr)
DSC_9051 by Greg Gorman (cc) (from Flickr)

At last week’s IBM Smarter Computing Forum we had a session on Watson, IBM’s artificial intelligence machine which won Jeopardy last year and another session on IBM sponsored research helping to create the SyNAPSE digital neuromorphic computing chip.

Putting “Watson to work”

Apparently, IBM is taking Watson’s smarts and applying it to health care and other information intensive verticals (intelligence, financial services, etc.).  At the conference IBM had Monoj Saxena, senior director Watson Solutions and Dr. Herbert Chase, a professor of clinical medicine a senior medical professor from Columbia School of Medicine come up and talk about Watson in healthcare.

Mr. Saxena’s contention and Dr. Chase concurred that Watson can play at important part in helping healthcare apply current knowledge.  Watson’s core capability is the ability to ingest and make sense of information and then be able to apply that knowledge.  In this case, using medical research knowledge to help diagnose patient problems.

Dr. Chase had been struck at a young age by one patient that had what appeared to be an incurable and unusual disease.  He was an intern at the time and was given the task to diagnose her issue.  Eventually, he was able to provide a proper diagnosis but it irked him that it took so long and so many doctors to get there.

So as a test of Watson’s capabilities, Dr. Chase input this person’s medical symptoms into Watson and it was able to provide a list of potential diagnosises.  Sure enough, Watson did list the medical problem the patient actually had those many years ago.

At the time, I mentioned to another analyst that Watson seemed to represent the end game of artificial intelligence. Almost a final culmination and accumulation of 60 years in AI research, creating a comprehensive service offering for a number of verticals.

That’s all great, but it’s time to move on.

SyNAPSE is born

In the next session IBM had Dr. Dharmenrad Modta come up and talk about their latest SyNAPSE chip, a new neueromorphic digital silicon chip that mimicked the brain to model neurological processes.

We are quite a ways away from productization of the SyNAPSE chip.  Dr. Modha showed us a real-time exhibition of the SyNAPSE chip in action (connected to his laptop) with it interpreting a handwritten numeral into it’s numerical representation.  I would say it’s a bit early yet, to see putting “SyNAPSE to work”.

Digital vs. analog redux

I have written about the SyNAPSE neuromorphic chip and a competing technology, the direct analog simulation of neural processes before (see IBM introduces SyNAPSE chip and MIT builds analog synapse chip).  In the MIT brain chip post I discussed the differences between the two approaches focusing on the digital vs. analog divide.

It seems that IBM research is betting on digital neuromorphic computing.  At the Forum last week, I had a discussion with a senior exec in IBM’s STG group, who said that the history of electronic computing over the last half century or so has been mostly about the migration from analog to digital technologies.

Yes, but that doesn’t mean that digital is better, just more easy to produce.

On that topic, I asked the Dr. Modha, on what he thought of MIT’s analog brain chip.  He said

  • MIT’s brain chip was built on 180nm fabrication processes whereas his is on 45nm or over 3X finer. Perhaps the fact that IBM has some of the best fab’s in the world may have something to do with this.
  • The digital SyNAPSE chip can potentially operate at 5.67Ghz and will be absolutely faster than any analog brain simulation.   Yes, but each analog simulated neuron is actually one of a parallel processing complex and with a 1’000 or a million of them operating even 1000X or million X slower it’s should be able to keep up.
  • The digital SyNAPSE chip was carefully designed to be complementary to current digital technology.   As I look at IT today we are surrounded by analog devices that interface very well with the digital computing environment, so I don’t think this will be a problem when we are ready to use it.

Analog still surrounds us and defines the real world.  Someday the computing industry will awaken from it’s digital hobby horse and somehow see the truth in that statement.

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In any case, if it takes another 60 years to productize one of these technologies then the Singularity is farther away than I thought, somewhere around 2071 should about do it.

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