Wednesday, 13 March 2019 22:52

IBM Research finds way to detect Alzheimer's disease early via ML-based blood test Featured


Australian researchers for global tech company IBM have applied machine learning to identify proteins in blood that can predict Alzheimer’s disease risk.

Alzheimer’s disease is a terminal neurodegenerative disease that has historically been diagnosed based on observing significant memory loss. There is currently no cure or disease-modifying therapy, despite hundreds of clinical trials.

It is thought these trials may have a high failure rate because the people enrolled are in the last stages of the disease, likely already suffering a level of brain tissue loss that cannot easily be repaired.

Thus, researchers have put their mind to how to detect this disease earlier, while a chance may still exist to slow its progression.

Recent research has shown a biological marker associated with the disease, a peptide called amyloid-beta, changes decades before any memory-related issues are apparent. Examining the concentration of the peptide in a person’s spinal fluid can provide an indication of Alzheimer’s disease risk decades before any memory-related issues are apparent.

Yet, accessing spinal fluid is highly invasive, requires an anaesthetist and is expensive.

IBM researchers released a paper this week detailing their work in employing machine learning to identify a set of proteins in blood that can predict the concentration of amyloid-beta in spinal fluid.

That is, the work could one day help clinicians predict the risk of Alzheimer’s in their patients, decades prior to any memory effects, through a simple and routine blood test.

The study isn’t the only one exploring a blood test for Alzheimer’s, but it is the first to use a machine learning approach to identify sets of proteins in blood that are predictive of a biomarker in spinal fluid.

The research is still in its early phases, but could potentially help improve the selection of individuals for Alzheimer’s disease drug trials, and the machine learning approach can be extended to model other spinal fluid-based biomarkers.

The researchers will present their work on a blood test for another key Alzheimer’s biomarker, tau, in Lisbon during a conference from 26 to 31 March.


26-27 February 2020 | Hilton Brisbane

Connecting the region’s leading data analytics professionals to drive and inspire your future strategy

Leading the data analytics division has never been easy, but now the challenge is on to remain ahead of the competition and reap the massive rewards as a strategic executive.

Do you want to leverage data governance as an enabler?Are you working at driving AI/ML implementation?

Want to stay abreast of data privacy and AI ethics requirements? Are you working hard to push predictive analytics to the limits?

With so much to keep on top of in such a rapidly changing technology space, collaboration is key to success. You don't need to struggle alone, network and share your struggles as well as your tips for success at CDAO Brisbane.

Discover how your peers have tackled the very same issues you face daily. Network with over 140 of your peers and hear from the leading professionals in your industry. Leverage this community of data and analytics enthusiasts to advance your strategy to the next level.

Download the Agenda to find out more


David M Williams

David has been computing since 1984 where he instantly gravitated to the family Commodore 64. He completed a Bachelor of Computer Science degree from 1990 to 1992, commencing full-time employment as a systems analyst at the end of that year. David subsequently worked as a UNIX Systems Manager, Asia-Pacific technical specialist for an international software company, Business Analyst, IT Manager, and other roles. David has been the Chief Information Officer for national public companies since 2007, delivering IT knowledge and business acumen, seeking to transform the industries within which he works. David is also involved in the user group community, the Australian Computer Society technical advisory boards, and education.



Recent Comments