A.I. Shows Promise as a Physician Assistant - The New York Times

Gerrit Jager gerrit.jager at PLANET.NL
Tue Feb 12 19:13:53 UTC 2019


Hi Mike,

It was a last year podcast:
https://www.itnonline.com/content/podcast-imaging-smack-down-siim-ai-won%E2%
80%99t-soon-replace-radiologists-eliot-siegel

‘It’s ridiculous to think that in the coming two decades,
artificial intelligence will replace radiologists, says AI expert Eliot
Siegel, M.D. <http://www.medschool.umaryland.edu/profiles/Siegel-Eliot/>
Even if AI got good at reading medical images, “radiologists do much more
than that,” he says in a podcast interview with Contributing Editor Greg
Freiherr. Listen to the podcast.
<https://soundcloud.com/user-787893434/podcast-imaging-smack-down-at-siim-ai
-wont-soon-replace-radiologists-with-eliot-siegel>  You can also view
Freiherr's video with Siegel, VIDEO INTERVIEW: Imaging Smack Down at SIIM:
AI Won't Soon Replace Radiologists, Says Expert
<https://www.itnonline.com/videos/video-interview-imaging-smack-down-siim-ai
-wont-soon-replace-radiologists-says-expert> , here
<https://www.itnonline.com/videos/video-interview-imaging-smack-down-siim-ai
-wont-soon-replace-radiologists-says-expert> .

In the accompanying video interview, Siegel, a radiology professor at the
University of Maryland School of Medicine
<http://www.medschool.umaryland.edu/>  and chief of Imaging Services at the
VA Maryland Health Care System, will highlight these and other reasons why
it’s ridiculous to think computers will replace radiologists. ‘


Gerrit


Op 12-02-19 16:39, Bruno, Michael <mbruno at PENNSTATEHEALTH.PSU.EDU> schreef:

> Dr. Eliot Siegel, a professor emeritus (I think) of Radiology from the U of
> Maryland, published a paper not too long ago (which I can’t find to reference
> at the moment) that AI is being asked a very different question than
> physicians are.  AI is only asked to emulate physician decision making,
> whereas physicians are asked to care for patients.  This difference has
> profound implications regarding the expectations we should place on such
> systems. 
>  
> Mike
>  
>  
> 
> From: Jason Maude [mailto:jason.maude at ISABELHEALTHCARE.COM]
> Sent: Tuesday, February 12, 2019 10:06 AM
> To: IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG
> Subject: Re: [IMPROVEDX] A.I. Shows Promise as a Physician Assistant - The New
> York Times 
>  
>  
> I think it depends on what the system sets out to do. If it intends to come up
> with the definitive diagnosis or a specific recommendation then that is more
> of an issue. If the system is just designed to come up with a short list for
> the clinician to consider and its made easy for the clinician to read up on
> the suggestions then that shouldn’t be an issue.
>  
> As we also know from the extensive work on biases, the human mind is far more
> of a black box than any of these systems!
>  
> Regards
> Jason
>  
> Jason Maude
> Founder and CEO Isabel Healthcare
> Tel: +44 1428 644886
> Tel: +1 703 879 1890
> www.isabelhealthcare.com
> <https://urldefense.proofpoint.com/v2/url?u=http-3A__www.isabelhealthcare.com_
> &d=DwMGaQ&c=_FmMnDvUH5queZcSmOuBzHZMbp7E7EwtGwv5cxxnTj0&r=XZJky8Jx0OuETXcWpBMh
> x9j_wSYpSZPDVXdInJ5O9gQ&m=J61V89oG0ArMKQ_hwBqxs52q7tSX0lSOHGNDblnv4Uw&s=Vot3we
> 8LSa_seDDeZJgs_m9s9YNPVOrIV-jvLFuqmPw&e=>
>  
>  
> 
> From: Edward Hoffer <ehoffer at GMAIL.COM>
> Reply-To: Society to Improve Diagnosis in Medicine
> <IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG>, Edward Hoffer <ehoffer at GMAIL.COM>
> Date: Tuesday, 12 February 2019 at 14:45
> To: "IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG"
> <IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG>
> Subject: Re: [IMPROVEDX] A.I. Shows Promise as a Physician Assistant - The New
> York Times
> 
>  
> 
> Fascinating study.  The biggest problem with neural networks is their opacity
> - inability to explain in a comprehensible way why/how they reach their
> conclusions - which makes many reluctant to accept their conclusions.  The
> biggest problem with a "big data" approach is that one may be finding
> correlations rather than cause and effect, and correlation does not prove
> causation.  Only when these systems can explain their reasoning will they be
> widely accepted. 
> 
> Ed
> 
> Edward P Hoffer MD
> 
> Co-creator, DXplain
>  
> 
> On Mon, Feb 11, 2019 at 11:17 PM HM Epstein <hmepstein at gmail.com> wrote:
>  
>> 
>> I still believe that AI is there to help, not take over. But still an
>> interesting article.
>> https://www.nytimes.com/2019/02/11/health/artificial-intelligence-medical-dia
>> gnosis.html 
>> <https://urldefense.proofpoint.com/v2/url?u=https-3A__www.nytimes.com_2019_02
>> _11_health_artificial-2Dintelligence-2Dmedical-2Ddiagnosis.html&d=DwMGaQ&c=_F
>> mMnDvUH5queZcSmOuBzHZMbp7E7EwtGwv5cxxnTj0&r=XZJky8Jx0OuETXcWpBMhx9j_wSYpSZPDV
>> XdInJ5O9gQ&m=J61V89oG0ArMKQ_hwBqxs52q7tSX0lSOHGNDblnv4Uw&s=LoJWgdO6Ch9enk6YuJ
>> Krj2Gmf2d_fKQkFNPkDwq6QWs&e=>
>> 
>>  
>> 
>> Best,
>> 
>> Helene 
>> 
>>  
>> 
>>        
>> 
>> Website 
>> <https://urldefense.proofpoint.com/v2/url?u=http-3A__hmepstein.com_&d=DwMGaQ&
>> c=_FmMnDvUH5queZcSmOuBzHZMbp7E7EwtGwv5cxxnTj0&r=XZJky8Jx0OuETXcWpBMhx9j_wSYpS
>> ZPDVXdInJ5O9gQ&m=J61V89oG0ArMKQ_hwBqxs52q7tSX0lSOHGNDblnv4Uw&s=AJE-aiOI_CDgeI
>> j0p9WAlKYl27cajT50Y5iNY4N9BXc&e=>  Twitter
>> <https://urldefense.proofpoint.com/v2/url?u=https-3A__twitter.com_hmepstein&d
>> =DwMGaQ&c=_FmMnDvUH5queZcSmOuBzHZMbp7E7EwtGwv5cxxnTj0&r=XZJky8Jx0OuETXcWpBMhx
>> 9j_wSYpSZPDVXdInJ5O9gQ&m=J61V89oG0ArMKQ_hwBqxs52q7tSX0lSOHGNDblnv4Uw&s=cNUBxA
>> PLRtze7l2pemPC1-Q3HHMS7tB3M5jrbHfg5dc&e=>
>> 
>> LinkedIn 
>> <https://urldefense.proofpoint.com/v2/url?u=https-3A__www.linkedin.com_in_hel
>> enekepstein_&d=DwMGaQ&c=_FmMnDvUH5queZcSmOuBzHZMbp7E7EwtGwv5cxxnTj0&r=XZJky8J
>> x0OuETXcWpBMhx9j_wSYpSZPDVXdInJ5O9gQ&m=J61V89oG0ArMKQ_hwBqxs52q7tSX0lSOHGNDbl
>> nv4Uw&s=BSCDYl70bnQ26oJCqlTTt6mfM42_YicLoAkZMNQMUMs&e=>
>> 
>>>> Facebook 
>> <https://urldefense.proofpoint.com/v2/url?u=https-3A__www.facebook.com_Helene
>> EpsteinAuthor&d=DwMGaQ&c=_FmMnDvUH5queZcSmOuBzHZMbp7E7EwtGwv5cxxnTj0&r=XZJky8
>> Jx0OuETXcWpBMhx9j_wSYpSZPDVXdInJ5O9gQ&m=J61V89oG0ArMKQ_hwBqxs52q7tSX0lSOHGNDb
>> lnv4Uw&s=aut235gnkic9a6dKJgMVeOYpMJh2eSr-YKiQ3hthSgc&e=>
>>  
>> 
>> A.I. Shows Promise as a Physician Assistant
>> Feb. 11, 2019
>> 
>> Doctors competed against A.I. computers to recognize illnesses on magnetic
>> resonance images of a human brain during a competition in Beijing last year.
>> The human doctors lost.
>> 
>> 
>> 
>> Each year, millions of Americans walk out of a doctor’s office with a
>> misdiagnosis 
>> <https://urldefense.proofpoint.com/v2/url?u=https-3A__www.sciencedaily.com_re
>> leases_2014_04_140416190948.htm&d=DwMGaQ&c=_FmMnDvUH5queZcSmOuBzHZMbp7E7EwtGw
>> v5cxxnTj0&r=XZJky8Jx0OuETXcWpBMhx9j_wSYpSZPDVXdInJ5O9gQ&m=J61V89oG0ArMKQ_hwBq
>> xs52q7tSX0lSOHGNDblnv4Uw&s=8gRsEWrHg920sqgHTJYIBPL2MDPgM5QFs1tTG4O8crw&e=> .
>> Physicians try to be systematic when identifying illness and disease, but
>> bias creeps in. Alternatives are overlooked.
>> Now a group of researchers in the United States and China has tested a
>> potential remedy for all-too-human frailties: artificial intelligence.
>> In a paper published on Monday in Nature Medicine, the scientists reported
>> that they had built a system that automatically diagnoses common childhood
>> conditions 
>> <https://urldefense.proofpoint.com/v2/url?u=https-3A__www.nature.com_articles
>> _s41591-2D018-2D0335-2D9&d=DwMGaQ&c=_FmMnDvUH5queZcSmOuBzHZMbp7E7EwtGwv5cxxnT
>> j0&r=XZJky8Jx0OuETXcWpBMhx9j_wSYpSZPDVXdInJ5O9gQ&m=J61V89oG0ArMKQ_hwBqxs52q7t
>> SX0lSOHGNDblnv4Uw&s=4siUOBu6PAlvUe3D9zW6Ha_mdpDMwafqZm6U9XTL45s&e=>  — from
>> influenza to meningitis — after processing the patient’s symptoms, history,
>> lab results and other clinical data.
>> The system was highly accurate, the researchers said, and one day may assist
>> doctors in diagnosing complex or rare conditions.
>> 
>> Drawing on the records of nearly 600,000 Chinese patients who had visited a
>> pediatric hospital over an 18-month period, the vast collection of data used
>> to train this new system highlights an advantage for China in the worldwide
>> race toward artificial intelligence.
>> Because its population is so large — and because its privacy norms put fewer
>> restrictions on the sharing of digital data — it may be easier for Chinese
>> companies and researchers to build and train the “deep learning” systems that
>> are rapidly changing the trajectory of health care.
>> On Monday, President Trump signed an executive order
>> <https://urldefense.proofpoint.com/v2/url?u=https-3A__www.nytimes.com_2019_02
>> _11_business_ai-2Dartificial-2Dintelligence-2Dtrump.html-3Fmodule-3Dinline&d=
>> DwMGaQ&c=_FmMnDvUH5queZcSmOuBzHZMbp7E7EwtGwv5cxxnTj0&r=XZJky8Jx0OuETXcWpBMhx9
>> j_wSYpSZPDVXdInJ5O9gQ&m=J61V89oG0ArMKQ_hwBqxs52q7tSX0lSOHGNDblnv4Uw&s=KDZkTPj
>> 1w7yyDJsips6pl7uAV34ufWBUmvnCqOa6IxY&e=>  meant to spur the development of
>> A.I. across government, academia and industry in the United States. As part
>> of this “American A.I. Initiative,” the administration will encourage federal
>> agencies and universities to share data that can drive the development of
>> automated systems.
>> Pooling health care data is a particularly difficult endeavor. Whereas
>> researchers went to a single Chinese hospital for all the data they needed to
>> develop their artificial-intelligence system, gathering such data from
>> American facilities is rarely so straightforward.
>> “You have go to multiple places,” said Dr. George Shih, associate professor
>> of clinical radiology at Weill Cornell Medical Center and co-founder of
>> MD.ai, a company that helps researchers label data for A.I. services. “The
>> equipment is never the same. You have to make sure the data is anonymized.
>> Even if you get permission, it is a massive amount of work.”
>> 
>> After reshaping internet services, consumer devices and driverless cars in
>> the early part of the decade, deep learning is moving rapidly into myriad
>> areas of health care. Many organizations, including Google
>> <https://urldefense.proofpoint.com/v2/url?u=https-3A__ai.googleblog.com_2018_
>> 05_deep-2Dlearning-2Dfor-2Delectronic-2Dhealth.html&d=DwMGaQ&c=_FmMnDvUH5queZ
>> cSmOuBzHZMbp7E7EwtGwv5cxxnTj0&r=XZJky8Jx0OuETXcWpBMhx9j_wSYpSZPDVXdInJ5O9gQ&m
>> =J61V89oG0ArMKQ_hwBqxs52q7tSX0lSOHGNDblnv4Uw&s=OBBmv_3JcvqbNU4vhcQt_jj2mk6UuJ
>> m1F-pk_kUY0Uk&e=> , are developing and testing systems that analyze
>> electronic health records in an effort to flag medical conditions such as
>> osteoporosis, diabetes, hypertension and heart failure.
>> Similar technologies are being built to automatically detect signs of illness
>> and disease in X-rays, M.R.I.s and eye scans.
>> The new system relies on a neural network
>> <https://urldefense.proofpoint.com/v2/url?u=https-3A__www.nytimes.com_2018_03
>> _06_technology_google-2Dartificial-2Dintelligence.html-3Fmodule-3Dinline&d=Dw
>> MGaQ&c=_FmMnDvUH5queZcSmOuBzHZMbp7E7EwtGwv5cxxnTj0&r=XZJky8Jx0OuETXcWpBMhx9j_
>> wSYpSZPDVXdInJ5O9gQ&m=J61V89oG0ArMKQ_hwBqxs52q7tSX0lSOHGNDblnv4Uw&s=Ez3xkko_C
>> IPtGAxda5M-xO145799p5lPziMzRCZoG4U&e=> , a breed of artificial intelligence
>> that is accelerating the development of everything from health care to
>> driverless cars 
>> <https://urldefense.proofpoint.com/v2/url?u=https-3A__www.nytimes.com_2018_01
>> _04_technology_self-2Ddriving-2Dcars-2Daurora.html-3Fmodule-3Dinline&d=DwMGaQ
>> &c=_FmMnDvUH5queZcSmOuBzHZMbp7E7EwtGwv5cxxnTj0&r=XZJky8Jx0OuETXcWpBMhx9j_wSYp
>> SZPDVXdInJ5O9gQ&m=J61V89oG0ArMKQ_hwBqxs52q7tSX0lSOHGNDblnv4Uw&s=UKoj-1cXT1Vza
>> z2ctMGV6DGKcw16BxMBeGzyaGihjPM&e=>  to military applications
>> <https://urldefense.proofpoint.com/v2/url?u=https-3A__www.nytimes.com_2018_02
>> _20_technology_artificial-2Dintelligence-2Drisks.html-3Fmodule-3Dinline&d=DwM
>> GaQ&c=_FmMnDvUH5queZcSmOuBzHZMbp7E7EwtGwv5cxxnTj0&r=XZJky8Jx0OuETXcWpBMhx9j_w
>> SYpSZPDVXdInJ5O9gQ&m=J61V89oG0ArMKQ_hwBqxs52q7tSX0lSOHGNDblnv4Uw&s=yfU1GxL4qz
>> 9dhJH8t4Lqnxe7amgibdm6ZUQAPc-CnAs&e=> . A neural network can learn tasks
>> largely on its own by analyzing vast amounts of data.
>> Using the technology, Dr. Kang Zhang, chief of ophthalmic genetics at the
>> University of California, San Diego, has built systems that can analyze eye
>> scans for hemorrhages, lesions and other signs of diabetic blindness.
>> Ideally, such systems would serve as a first line of defense, screening
>> patients and pinpointing those who need further attention.
>> Now Dr. Zhang and his colleagues have created a system that can diagnose an
>> even wider range of conditions by recognizing patterns in text, not just in
>> medical images. This may augment what doctors can do on their own, he said.
>> “In some situations, physicians cannot consider all the possibilities,” he
>> said. “This system can spot-check and make sure the physician didn’t miss
>> anything.”
>> The experimental system analyzed the electronic medical records of nearly
>> 600,000 patients at the Guangzhou Women and Children’s Medical Center in
>> southern China, learning to associate common medical conditions with specific
>> patient information gathered by doctors, nurses and other technicians.
>> 
>> First, a group of trained physicians annotated the hospital records, adding
>> labels that identified information related to certain medical conditions. The
>> system then analyzed the labeled data.
>> Then the neural network was given new information, including a patient’s
>> symptoms as determined during a physical examination. Soon it was able to
>> make connections on its own between written records and observed symptoms.
>> When tested on unlabeled data, the software could rival the performance of
>> experienced physicians. It was more than 90 percent accurate at diagnosing
>> asthma; the accuracy of physicians in the study ranged from 80 to 94 percent.
>> In diagnosing gastrointestinal disease, the system was 87 percent accurate,
>> compared with the physicians’ accuracy of 82 to 90 percent.
>> Able to recognize patterns in data that humans could never identify on their
>> own, neural networks can be enormously powerful in the right situation. But
>> even experts have difficulty understanding why such networks make particular
>> decisions and how they teach themselves.
>> As a result, extensive testing is needed to reassure both doctors and
>> patients that these systems are reliable.
>> Experts said extensive clinical trials are now needed for Dr. Zhang’s system,
>> given the difficulty of interpreting decisions made by neural networks.
>> 
>> “Medicine is a slow-moving field,” said Ben Shickel, a researcher at the
>> University of Florida who specializes in the use of deep learning for health
>> care. “No one is just going to deploy one of these techniques without
>> rigorous testing that shows exactly what is going on.”
>> It could be years before deep-learning systems are deployed in emergency
>> rooms and clinics. But some are closer to real-world use: Google is now
>> running clinical trials of its eye-scan system at two hospitals in southern
>> India.
>> Deep-learning diagnostic tools are more likely to flourish in countries
>> outside the United States, Dr. Zhang said. Automated screening systems may be
>> particularly useful in places where doctors are scarce, including in India
>> and China.
>> The system built by Dr. Zhang and his colleagues benefited from the large
>> scale of the data set gathered from the hospital in Guangzhou. Similar data
>> sets from American hospitals are typically smaller, both because the average
>> hospital is smaller and because regulations make it difficult to pool data
>> from multiple facilities.
>> Dr. Zhang said he and his colleagues were careful to protect patients’
>> privacy in the new study. But he acknowledged that researchers in China may
>> have an advantage when it comes to collecting and analyzing this kind of
>> data.
>> “The sheer size of the population — the sheer size of the data — is a big
>> difference,” he said.
>>  
>>  
>> 
>> 
>> 
>> 
>> To unsubscribe from IMPROVEDX: click the following link:
>> http://list.improvediagnosis.org/scripts/wa-IMPDIAG.exe?SUBED1=IMPROVEDX&A=1
>> <https://urldefense.proofpoint.com/v2/url?u=http-3A__list.improvediagnosis.or
>> g_scripts_wa-2DIMPDIAG.exe-3FSUBED1-3DIMPROVEDX-26A-3D1&d=DwMGaQ&c=_FmMnDvUH5
>> queZcSmOuBzHZMbp7E7EwtGwv5cxxnTj0&r=XZJky8Jx0OuETXcWpBMhx9j_wSYpSZPDVXdInJ5O9
>> gQ&m=J61V89oG0ArMKQ_hwBqxs52q7tSX0lSOHGNDblnv4Uw&s=81LK7MHaf82gYNiwT3U7_Nc9nY
>> X7-OyXFH-GRpz-m6Y&e=>  or send email to:
>> IMPROVEDX-SIGNOFF-REQUEST at LIST.IMPROVEDIAGNOSIS.ORG
>> 
>> <https://urldefense.proofpoint.com/v2/url?u=http-3A__list.improvediagnosis.or
>> g_scripts_wa-2DIMPDIAG.exe-3FINDEX&d=DwMGaQ&c=_FmMnDvUH5queZcSmOuBzHZMbp7E7Ew
>> tGwv5cxxnTj0&r=XZJky8Jx0OuETXcWpBMhx9j_wSYpSZPDVXdInJ5O9gQ&m=J61V89oG0ArMKQ_h
>> wBqxs52q7tSX0lSOHGNDblnv4Uw&s=gCC6tP05IDCdsqtWOjNrfkcv180bTz1amZL61Xl8H1M&e=>
>> Moderator:David Meyers, Board Member, Society for Improving Diagnosis in
>> Medicine
>> 
>> To learn more about SIDM visit:
>> http://www.improvediagnosis.org/
>> <https://urldefense.proofpoint.com/v2/url?u=http-3A__www.improvediagnosis.org
>> _&d=DwMGaQ&c=_FmMnDvUH5queZcSmOuBzHZMbp7E7EwtGwv5cxxnTj0&r=XZJky8Jx0OuETXcWpB
>> Mhx9j_wSYpSZPDVXdInJ5O9gQ&m=J61V89oG0ArMKQ_hwBqxs52q7tSX0lSOHGNDblnv4Uw&s=rlm
>> KzBJJivcHS2dI02LkcqrolbUD8dsROd0954MNsk0&e=>
>>  
>> 
>> 
>> 
>> 
>> 
>> To unsubscribe from IMPROVEDX: click the following link:
>> http://list.improvediagnosis.org/scripts/wa-IMPDIAG.exe?SUBED1=IMPROVEDX&A=1
>> <https://urldefense.proofpoint.com/v2/url?u=http-3A__list.improvediagnosis.or
>> g_scripts_wa-2DIMPDIAG.exe-3FSUBED1-3DIMPROVEDX-26A-3D1&d=DwMGaQ&c=_FmMnDvUH5
>> queZcSmOuBzHZMbp7E7EwtGwv5cxxnTj0&r=XZJky8Jx0OuETXcWpBMhx9j_wSYpSZPDVXdInJ5O9
>> gQ&m=J61V89oG0ArMKQ_hwBqxs52q7tSX0lSOHGNDblnv4Uw&s=81LK7MHaf82gYNiwT3U7_Nc9nY
>> X7-OyXFH-GRpz-m6Y&e=>
>> or send email to: IMPROVEDX-SIGNOFF-REQUEST at LIST.IMPROVEDIAGNOSIS.ORG
>> 
>> <https://urldefense.proofpoint.com/v2/url?u=http-3A__list.improvediagnosis.or
>> g_scripts_wa-2DIMPDIAG.exe-3FINDEX&d=DwQGaQ&c=_FmMnDvUH5queZcSmOuBzHZMbp7E7Ew
>> tGwv5cxxnTj0&r=XZJky8Jx0OuETXcWpBMhx9j_wSYpSZPDVXdInJ5O9gQ&m=J61V89oG0ArMKQ_h
>> wBqxs52q7tSX0lSOHGNDblnv4Uw&s=gCC6tP05IDCdsqtWOjNrfkcv180bTz1amZL61Xl8H1M&e=>
>> 
>> Moderator:David Meyers, Board Member, Society for Improving Diagnosis in
>> Medicine
>> 
>> To learn more about SIDM visit:
>> http://www.improvediagnosis.org/
>> <https://urldefense.proofpoint.com/v2/url?u=http-3A__www.improvediagnosis.org
>> _&d=DwQGaQ&c=_FmMnDvUH5queZcSmOuBzHZMbp7E7EwtGwv5cxxnTj0&r=XZJky8Jx0OuETXcWpB
>> Mhx9j_wSYpSZPDVXdInJ5O9gQ&m=J61V89oG0ArMKQ_hwBqxs52q7tSX0lSOHGNDblnv4Uw&s=rlm
>> KzBJJivcHS2dI02LkcqrolbUD8dsROd0954MNsk0&e=>
>>  
>> 
>> 
>> 
>> 
>> To unsubscribe from IMPROVEDX: click the following link:
>> http://list.improvediagnosis.org/scripts/wa-IMPDIAG.exe?SUBED1=IMPROVEDX&A=1
>> <https://urldefense.proofpoint.com/v2/url?u=http-3A__list.improvediagnosis.or
>> g_scripts_wa-2DIMPDIAG.exe-3FSUBED1-3DIMPROVEDX-26A-3D1&d=DwMGaQ&c=_FmMnDvUH5
>> queZcSmOuBzHZMbp7E7EwtGwv5cxxnTj0&r=XZJky8Jx0OuETXcWpBMhx9j_wSYpSZPDVXdInJ5O9
>> gQ&m=J61V89oG0ArMKQ_hwBqxs52q7tSX0lSOHGNDblnv4Uw&s=81LK7MHaf82gYNiwT3U7_Nc9nY
>> X7-OyXFH-GRpz-m6Y&e=>
>> or send email to: IMPROVEDX-SIGNOFF-REQUEST at LIST.IMPROVEDIAGNOSIS.ORG
>> 
>> <https://urldefense.proofpoint.com/v2/url?u=http-3A__list.improvediagnosis.or
>> g_scripts_wa-2DIMPDIAG.exe-3FINDEX&d=DwQGaQ&c=_FmMnDvUH5queZcSmOuBzHZMbp7E7Ew
>> tGwv5cxxnTj0&r=XZJky8Jx0OuETXcWpBMhx9j_wSYpSZPDVXdInJ5O9gQ&m=J61V89oG0ArMKQ_h
>> wBqxs52q7tSX0lSOHGNDblnv4Uw&s=gCC6tP05IDCdsqtWOjNrfkcv180bTz1amZL61Xl8H1M&e=>
>> 
>> Moderator:David Meyers, Board Member, Society for Improving Diagnosis in
>> Medicine
>> 
>> To learn more about SIDM visit:
>> http://www.improvediagnosis.org/
>> <https://urldefense.proofpoint.com/v2/url?u=http-3A__www.improvediagnosis.org
>> _&d=DwQGaQ&c=_FmMnDvUH5queZcSmOuBzHZMbp7E7EwtGwv5cxxnTj0&r=XZJky8Jx0OuETXcWpB
>> Mhx9j_wSYpSZPDVXdInJ5O9gQ&m=J61V89oG0ArMKQ_hwBqxs52q7tSX0lSOHGNDblnv4Uw&s=rlm
>> KzBJJivcHS2dI02LkcqrolbUD8dsROd0954MNsk0&e=>
>> 
>> 
>> 
>> 
>> To unsubscribe from IMPROVEDX: click the following link:
>> http://list.improvediagnosis.org/scripts/wa-IMPDIAG.exe?SUBED1=IMPROVEDX&A=1
>>  or send email to: IMPROVEDX-SIGNOFF-REQUEST at LIST.IMPROVEDIAGNOSIS.ORG
>> 
>> 
>> Moderator:David Meyers, Board Member, Society for Improving Diagnosis in
>> Medicine
>> 
>> To learn more about SIDM visit:
>> http://www.improvediagnosis.org/
>> 







Moderator: David Meyers, Board Member, Society to Improve Diagnosis in Medicine


HTML Version:
URL: <../attachments/20190212/9905ff64/attachment.html>


More information about the Test mailing list