Sandor,
Did you perhaps mean screening 15,000,000 Caucasians would yield 300 melanomas?
But that should only be 75 melanomas.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4399142/
Uveal melanoma represents 79-81% of ocular melanomas and 3-5% of all
melanomas.[1<https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4399142/#ref1>,2<https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4399142/#ref2>,3<https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4399142/#ref3>]
In the United States, the incidence of uveal melanoma is 5/million population.
Tom
________________________________
From: optimal-bounce@xxxxxxxxxxxxx <optimal-bounce@xxxxxxxxxxxxx> on behalf of
Sandor Ferenczy <sandorferenczy@xxxxxxxxx>
Sent: Wednesday, February 21, 2018 9:38 AM
To: optimal@xxxxxxxxxxxxx
Subject: [optimal] Re: [**External**] Google and Ophthalmic Imaging Neural Nets
I more picture a self-guided imaging system next to the self-guided blood
pressure system @ the local pharmacy.
Imagine the power of screening tens of thousands of wide field, color images
with machine learning, abnormal findings whether vascular, nerve, retinal,
tumor can be forwarded directly to the existing reading centers @ the world's
best hospitals & patient be told to follow up with a local ophthalmologist.
In statistical work we have done, we estimate that screening of only 15,000
Caucasians in the US would yield 300 growing melanocytic tumors in the uvea.
...imagine...
No human could do intra ocluar screening as efficiently as a computer. we just
need to train them what to look for.
-sandor
On Wed, Feb 21, 2018 at 9:18 AM, joey hatfield
<bioartevolution@xxxxxxxxx<mailto:bioartevolution@xxxxxxxxx>> wrote:
Imagine, program guided self assessment fundus imaging on a phone that can send
a report to the physician. Evaluation of the posterior pole for this
application, diabetic changes, etc...AI is very real and being looked at
heavily by most major companies.
Joey Hatfield
Area Sales Consultant
Heidelberg Engineering
Mobile: 501-515-0697<tel:(501)%20515-0697>
email:
jhatfield@xxxxxxxxxxxxxxxxxxxxxxxxx<mailto:jhatfield@xxxxxxxxxxxxxxxxxxxxxxxxx>
10 Forge
Parkway<https://maps.google.com/?q=10+Forge+Parkway&entry=gmail&source=g> l
Franklin, MA l 02038
Tel:
Fax:
www.heidelbergengineering.com<http://www.heidelbergengineering.com>
www.spectralis.info<http://www.spectralis.info>
On Feb 21, 2018, at 8:06 AM, Sandor Ferenczy
<sandorferenczy@xxxxxxxxx<mailto:sandorferenczy@xxxxxxxxx>> wrote:
Neither fake news or bad science.
Machine learning (a computer's progressive improvement at a task based on
training rather than explicit programming) is real, has been around since the
'50s, and is more and more being applied to medicine.
The most important part of this general public article are the second two
paragraphs:
The algorithms didn’t outperform existing medical approaches such as blood
tests, according to a study of the finding published in the journal Nature
Biomedical Engineering. The work needs to be validated and repeated on more
people before it gains broader acceptance, several outside physicians said.
But the new approach could build on doctors’ current abilities by providing a
tool that people could one day use to quickly and easily screen themselves for
health risks that can contribute to heart disease, the leading cause of death
worldwide.
-sandor
On Tue, Feb 20, 2018 at 9:34 PM, CPMC Ophthalmic Diagnostic Center
<cpmceyelab@xxxxxxxxxxxxxxxx<mailto:cpmceyelab@xxxxxxxxxxxxxxxx>> wrote:
I am unclear as to how these poor Topcon images would help screen for stroke
Unless they are referring to H. Plaque, Occlusions, etc and the usual signs
that would send a patient for a Carotid angiogram.
Fake news or bad science?
Denice Barsness, CRA, COMT, CDOS, FOPS
CPMC Dept of Ophthalmology/ The Eye Institute
Ophthalmic Diagnostic Services
711 Van Ness Avenue Suite
250<https://maps.google.com/?q=711+Van+Ness+Avenue+Suite+250%0D+San+Francisco+CA+94109&entry=gmail&source=g>
San Francisco CA
94109<https://maps.google.com/?q=711+Van+Ness+Avenue+Suite+250%0D+San+Francisco+CA+94109&entry=gmail&source=g>
415-600-5781<tel:(415)%20600-5781>
FAX 415-558-7011<tel:(415)%20558-7011>
From: Barsness, Denice
Sent: Tuesday, February 20, 2018 3:30 PM
To: CPMC Ophthalmic Diagnostic Center
<cpmceyelab@xxxxxxxxxxxxxxxx<mailto:cpmceyelab@xxxxxxxxxxxxxxxx>>
Subject: FW: [**External**] [optimal] Google and Ophthalmic Imaging Neural Nets
________________________________
From: optimal-bounce@freelists.orgOn<mailto:optimal-bounce@freelists.orgOn>
Behalf Ofjmc eye photo
Sent: Tuesday, February 20, 2018 3:29:24 PM (UTC-08:00) Pacific Time (US &
Canada)
To: optimal@xxxxxxxxxxxxx<mailto:optimal@xxxxxxxxxxxxx>
Subject: [**External**] [optimal] Google and Ophthalmic Imaging Neural Nets
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Password.
Interesting article at link below. Article says images are scans, but the notch
says otherwise.
https://www.washingtonpost.com/news/the-switch/wp/2018/02/19/google-used-artificial-intelligence-to-predict-heart-attacks-with-the-human-eye/?utm_term=.27acdee9d2c2<https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.washingtonpost.com%2Fnews%2Fthe-switch%2Fwp%2F2018%2F02%2F19%2Fgoogle-used-artificial-intelligence-to-predict-heart-attacks-with-the-human-eye%2F%3Futm_term%3D.27acdee9d2c2&data=02%7C01%7Cbarsned%40sutterhealth.org%7C237d2f1935ba46f2cc4d08d578b9d510%7Caef453eadaa243e0be62818066e9ff63%7C0%7C0%7C636547661901797261&sdata=i1fWfksoNwte6wtgWc9U%2BHBQvewqDApiohRH7p0BCmQ%3D&reserved=0>
Anyone out there participating is such studies?
Richard Press posted about a similar project re diabetes last march.
ALSO — Is Google a sustaining member of OPS?
john michael coppinger
jmc eye photo
