What if you could watch aging reverse?

Warning: technical jargon ahead

 

Aging takes a long time. Rejuvenation aims to take a little less time. How long are you willing to wait?

How many ways might chronic pain, with its impairment of innate functions, accelerate aging?

Could a return back-to-normal function reverse aging?

____

PhotoMed’s team of nerdy software and hardware engineers uncomfortably backed into these questions. We still don’t have answers after 20 years and self-funding of $20M. Machine learning (ML) techniques uncovered a few interesting features of anti-aging. It may be that ML works more efficiently with events in real time rather than it works with slow processes.

 

Unexpected outcomes

The team’s task was to develop tools to test PhotoMed’s therapy with patients having “nothing worked” types of pain. Surgeries, medications, opioids, more surgeries, you get the picture.  The patient’s disorders were not expected to improve. (You can read about the therapy elsewhere on this website.)

 

Reversing diabetic numbness to avoid wounds and amputations.

 
 

Ending persistent post-surgical pain and “phantom” pain.

 
 

The engineers hooked up sensors and cameras to their computers. The tools recorded events in real time without the bias of a hypothesis. Most of the time nothing happened. At least there were no side effects beside disappointment.

The events were unexpected by the patient, like hands warming after 30-years of coldness.

The engineers were happy because it was so easy to detect when the therapy “works”.

Find a partial-list here.

 

Their anesthesiologist and neurologist advisors that they consulted were puzzled by the results. The outcomes appeared to be incompatible with current medical understanding and theories.

   

Could machine learning help us get lucky more often?

Silicon Valley thinking directed the engineers attention to things that happened quickly. The software engineers looked for binary outcomes. Did the patient respond, or not?

Machine learning recognized that the responses were not just masking pain. It seemed to be that a switch was being flipped. The improvements were deep in default systems. It was like that a hard disk was “defragged” and the operating systems went back-to-normal.

The engineers built tools for Intel before starting this adventure. Andy Grove taught us that only the paranoid survives. Just seeing it with own eyes meant nothing for our paranoid minds. We built tools to document in real time what was going on and when.


Without a hypothesis, it was time to be quiet. This wasn’t a science project. The task was to make the therapeutic algorithm more efficient.

InstantVerification2019-07-23.png
 

Early forms of machine learning helped the team to develop PhotoMed’s Triple 2 Algorithm by increasing the speed and predictability of the results. Our Silicon Valley roots demanded that the system design consider the delivery cost and complexity for the user and the patient.

Triple2AlgorithmV3.png
 


Pain is the biggest contributor to premature aging. (1)

Many people have permanent “nothing worked” pain. They may have tried everything available. The trying may have introduced new sources of pain. 1-in-12 knee replacement patients wish that they did not have the operation. (2)

We funded PhotoMed our exit from building tools to help reduce defect rates from 1-in-a million to 1-in-a billion.


The “nothing worked” types of pain present a low probability of resolution, close to zero, using conventional interventions. The yield from the Triple 2 Algorithm is about 1-in-3.

nothingWorkedPAIN.png
 

The engineers were surprised when machining learning (ML) found what the patient had been reporting. They said, “I feel normal again”. ML also found that the “back-to-normal” function appears to be independent of life’s variables.

back2NORMAL.png
 

People with less pain live happier longer lives.

 

______

Citations

(1) https://www.apa.org/pubs/journals/releases/amp-a0035794.pdf Molton IR,Terrill AL, Overview of Persistent Pain in Older Adults, American Psychologist, Vol 69(2), Feb-Mar 2014, 197-207, DOI: 10.1037/a0035794

(2) https://www.ncbi.nlm.nih.gov/pubmed/14659522 , Harden RN, et al, Prospective examination of pain-related and psychological predictors of CRPS-like phenomena following total knee arthroplasty: a preliminary study, Pain. 2003 Dec;106(3):393-400. DOI: https://insights.ovid.com/article/00006396-200312000-00020