Of AI and Healthcare - medconf.de · Artificial Intelligence Is it really intelligent? Sixties 2016...
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Of AI and Healthcare
Artificial Intelligence
Is it really intelligent?
Sixties 2016
PROGRESS?
Silver D. et al. Mastering the game of Go with deep neural networks and tree search.
Nature, (2016)
What is AI?
AI is an entity that thinks / actshumanely / rationally
Mathematics
Linguistic
Psychology
Philosophy
According to Russel's, Norvig's
"Artificial intellegence: A modern approach"
To Build an Intelligent AI We Have to Be Good at:
Robotics
Machine Learning
Natural Language Processing
Automated Reasoning
Knowledge Representation
Computer Vision
Healthcare is not only about healing people but also about making the
healing process as stress-free, easy and cheap
as possible
Microbiome modification
Aging
Disease diagnosis /
cure
Novelty drug development
If it is a terrifying thought that life is at the mercy of the multiplication of these minute bodies [microbes], it is a consoling hope that Science will not always remain powerless before such enemies...
Making Microbes Better
Louis Pasteur
Nobel Prize for Chemistry 2018
Millions years before Nowadays
NATURAL EVOLUTION
DIRECTED EVOLUTION
Change Microbes Intelligently
Zymergen
Creating artificial microbes that can create useful molecules
1013,000 ways in which microbe genes can be altered
Impact on:
Healthcare
Agriculture
Food industry
Material science
Change Microbes IntelligentlyFrom Robert W. Bauman, Microbiology With Diseases by Body System,
Benjamin Cummings, 2012
Input: Microbes
Machine LearningProcess
automatization
Traits improvement
REPEAT
Higher yield
Fasterfermentation
Newmaterials
Diagnoses Conundrum
Once you eliminate the impossible, whatever remains, no matter how improbable, must be the truth.
Sherlock Holmes
Patients can have as many diseases as they damn well please.
John Hickam, MD.
Why Do We Need AI to Make a Diagnosis?
From Ashley N. D. Meyer et.al. Physicians’ Diagnostic Accuracy, Confidence,
and Resource Requests A Vignette Study
JAMA Inter.Med, (2013)
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History Physical General Lab and Imaging Definitive Lab and Imaging
Case Difficulty Gap(Confidence – Accuracy)
Easy More Difficult
The cost of medical errors
Evolution of the Diagnosis Support Engine
70s 90s – Nowadays
Sore throat
Erythema?
Pus?
Adenopathy?
Streptococcal pharyngitis
Non-infectious Cause
Viral pharyngitis
Viral pharyngitis
No
No
No
Yes
Yes
Yes
Myocardial infarction
Cardiac arrhythmia
ST Segment depression
Sinus tachycardia
Sinus bradycardia
Atrial fibrillation
Atrial flutter
Junctionalrhythm
AI vs. Human Doctors
Physicians diagnostic accuracy is 85-90% From Semigran, H. L., et.al. Comparison of Physician and Computer Diagnostic Accuracy, JAMA Internal Medicine, (2016)
Physician and Symptom Chekers’ Diagnostic Accuracy, Stratified by the Acuity Level and Prevalence of the Conditions Described by the Clinical Vignettes
Let’s Make a Diagnosis
A 47-year-old woman was brought to the emergency department by her family because of 1 week of abdominal pain. The pain had begun in the epigastrium but had spread across the abdomen. She described it as constant and 10 of 10 in intensity but could not identify aggravating or alleviating factors. She also complained of nausea and vomiting, beginning 4 days prior to presentation, occurring two to five times per day. She noted poor oral intake and mild diarrhea. She denied melena or hematochezia. She reported no recent fever, dysuria, chills, or night sweats; however, she reported upper respiratory symptoms 2 weeks prior to presentation. On the day of presentation, her family felt she was becoming increasingly lethargic.
The patient had a history of nephrolithiasis and had undergone total abdomi- nal hysterectomy and bilateral salpingo-oopherectomy secondary to uterine fibroids. She took occasional acetaminophen, smoked two cigarettes per day, and rarely con- sumed alcohol. Temperature was 38.5◦C, heart rate was 160 beats per minute, respiratory rate was 28/minute, and blood pressure was 92/52 mm Hg; oxygen saturation was 100% breathing 2 L of oxygen by nasal cannula. She was a moder-ately obese African-American woman in moderate distress, lying in bed moaning. Mucous membranes were dry. There was no lymphadenopathy or thyromegaly.
Ada’s doing its best
Symptoms reported as present
Abdominal painposition: epigastricintensity: severeeating: exacerbates defecation: no effecttime since onset: one day to one week
Nauseaintensity: moderate
time since onset: one day to one week
Vomitingunable to tolerate fluids: no forceful: no
time since onset: one day to one week
Fatiguetime since onset: less than one day
Diarrhea
time since onset: one day to one week blood: no
Feverhigh grade: no
time since onset: less than one day
Rapid pulsetime since onset: less than one day
Low blood pressuretime since onset: less than one day
Fast breathing
Symptoms reported as absent
Cholecystectomy
Tender abdomen
Swollen abdomen
Pale face
Loss of appetite
Unusual discolouration of stool Flank pain
Heartburn
Chest pain
Dizziness
Back pain
Urinating less
Headache
Dry mouth
General yellowing or darkening of the skin
Feeling of abdominal bloating Shoulder pain
Yellow eyes
Vomiting blood
Pregnant
Diabetes
High blood pressure
…still doing best
Mesenteric vein thrombosis
Seek emergency care
4 out of 10 people with these symptoms had this condition.
Liver abscess
Seek emergency care
1 out of 10 people with these symptoms had this condition.
SepsisSeek emergency care
7 out of 100 people with these symptoms had this condition.
Cholecystitis
Seek emergency care
3 out of 100 people with these symptoms had this condition.
Acute gastritis
Seek emergency care
3 out of 100 people with these symptoms had this condition.
But exact symptom is…
This case nicely demonstrates a key teaching point: a fast regular heart rate of about 150, irrespective of the electrocardiogram, suggests atrial flutter. Who gets atrial flutter? Patients with chronic lung disease, myocardial ischemia (albeit rarely), alcohol-induced cardiomyopathy, and infiltrative cardiac disorders. Additionally, we also have to consider thyroid dysfunction.
Thyroid studies revealed thyroid stimulating hormone of less than 0.01 mU/L (normal range, 0.30–5.50)
Grave’s disease
Understanding Diseases
To predict a disease =
find the structure of a Bayesian network
From Schadt, D.-S. Molecular networks as sensors and drivers of common human diseases,
Nature, (2009)
Understanding Diseases
From Lee, D.-S., et.al. The implications of human metabolic network topology for disease comorbidity,
PNAS, (2008)
AI Can Hear and Understand
HAL 9000: Dave, although you took very thorough precautions in the pod against my hearing you, I could see your lips move.The Cosmic Odyssey 2001,
Stanley Kubrick
She said, “Can you help me, Mr. Robot, sir?” The Talking Robot was designed to answer questions, and only such questions as it could answer had ever been put to it. It was quite confident of its ability, therefore, “I- can- help- you.”
Isaac Asimov,Robbie
"Nuttiest thing I ever heard of," said the President. "You have to punch out the questions on that thingamajig, and the answers come out on tape from the whatchamacallits. You can't just talk to it." A doubt crossed his fine face. "I mean, you can't, can you?” "No sir," said the chief engineer of the project. "As you say, not without the thingamajigs and whatchamacallits.”
Kurt Vonnegut, Player Piano
Physicians Spend 30% of their Time on Table Work
Just beneath the skin. Just above the heart. It records the heartbeat and sends out a signal and that signal is recorded on a monitor and when the signal stops a rescue squad is sent. ...and there it was, a little metallic thing, but it wasn't just a piece of metal; it was a man's life laying there.
Wearables in Healthcare
Clifford Simak,Why call them back from heaven
Wearables Boom
The global medical wearable devices market $3.2 billion in revenue 2016.
Is expected to cross $7.9 billionin 2021.
What Medical Wearable Devices Give Us
Structured Data
Large Volumes of Good Data
Continuous Health Control
Active vs. Reactive Medicine
Avoiding Critical States
What to Do with this Data?
Electrocardiogram
Oxygen saturation
Heart rate
Photoplethysmography
Blood glucose
Respiratory rate
Blood pressure
Body temperature
Vital sign parameters:
AI-Enabled Platform for Doctors to Improve Stroke Prevention
$30 million from Omron and Mayo Clinic
FDA approved
The Aging
AI plays not Go only.
Anton Dolgikh,DataArt
I think that even people past their 70s, who are in good health, have a fighting chance to live past 150.
Dr Alex Zhavoronkov, Director of the Biogerontology
Research Foundation
…to add life to years, not years to life
FINDING BIOMARKERS OF
AGING
GEROPROTECTIVE THERAPY
We need better drugs – now
Drug Development Race
Francis Collins, Director of theNational Institutes of Health, USA
The problem
The problemHow much of them can be treated with drugs?
The problem
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Goals of Using AI in Drug Search
Facilitate biopharmaceutical companies to accelerate development of drugs
New targets
Safe drug candidates
Novelty drugs
Neural Networks (GAN) and Drug Development Kadurin A. et al.
The cornucopia of meaningful leads: Applying deep adversarial autoencodersfor new molecule development in oncology.
Oncotarget, (2017)
Insilico Medicine
Pubchem
72 million of compounds
Neural network
69 moleculesWith known
biological activity
New compounds
The math is not enough.
Anton Dolgikh,DataArt
“I will do cheese in batter.”
“How is that made?”
“Facilis. You take the cheese before it is too antiquum, without too much salis, and cut in cubes or sicut you like. And postea you put a bit of butierro or lardo to rechauffer over the embers. And in it you put two pieces of cheese, and when it becomes tenero, zucharum et cinnamon supra positurum du bis. And immediately take to table, because it must be ate caldo caldo.”
Umberto Eco,The name of the rose
What hinders the adoption?
…political, fiscal or cultural nature rather than purely technical.
The Math is Not Enough
Edward Shortliffe in “The coming age of artificial intelligence in medicine”, 2009
The Words are Not Enough
20182008
From T.S. Field, et.al. Costs Associated with Developing and Implementing a Computerized Clinical Decision Support System for Medication Dosing for Patients with Renal Insufficiency in the Long-term Care Setting, JAMIA, 2008
Wonderful! But Where Can I Buy it?
Difficulties of adoption:
Words, words, words.
Problems
Dataset constructed incorrectly
Radiologists reports processed automatically but incorrectly
Validation by human experts conducted in a questionable way
Team didn’t have a medical expert
THE MAIN PROBLEM
RESUME
CheXNet is nowhere near ready to be deployed “in the wild”
Bailint Botz, MD/PhD,
Diagnostic radiology resident
But, yes, neural networks are state-of-the-art
Ain't that the damnedest thing you ever heard of? Takes seven of them. Now with us, it just takes a man and woman.
The Team to Succeed
Clifford Simak,Mirage
Whom to Hire
Data Scientist (statistician, mathematician)
Data Engineer
Subject-Matter-Expert
Quality Engineer
Project Manager
Visionaries, where are you?!
The technology exists today—including predictive analytics, robotic process automation, and AI-based tools, all digitally connected via the Internet of Things (IoT)—but no pharma company has fully leveraged it yet.
…
One needs visionaries - and not just pragmatists – to see the full potential of digitalization.
T. Dedeurwaerder, et.al. How data is changing the pharmaoperations world, McKinsey&Company,
August 2018
People can relax: Robot healthcare is not about to take over.
Roman Chernyshev, Senior Vice President,
Healthcare and Life Sciences, DataArt
And, unfortunately, we are not very good at anticipating what the next emerging serious flaw will be.
Michael Jordan in "Artificial Intelligence — The
Revolution Hasn’t Happened Yet", 2018
AI and Automation
But this is something that we have seen over and over in the last so many centuries, where a breakthrough in technology, a significant innovation, creates fear and anxiety, does eliminate jobs. But by the same token, new jobs are created. And this is most likely what we are going to see.
Chrisitne Lagardein the interview to the Wall Street Journal
New technologies – such as digitalization, artificial intelligence, and automation – have the potential to change the nature of production processes, raise productivity, and reshape labor markets.
…requires first understanding the role of technology in shaping new production processes, with the concomitant changes in terms of productivity and labor market relationships.
Group of Twenty, “Future of Work: Measurement and Policy Challenges”
2016 2018
Job Title Probability
Medical and Clinical Laboratory Technicians 47%
Epidemiologists 20%
Pharmacists 1.2%
Physicians and Surgeons 0.42%
Will Robots Take My Job?
Frey C. B., Osborne M. A. The future of employment: how susceptible are jobs to computerisation?, Technological Forecasting and Social Change.
(2017)
Job title Probability
Medical and Clinical Laboratory Technicians 47%
Epidemiologists 20%
Pharmacists 1.2%
Physicians and Surgeons 0.42%
Will Robots Take My Job?
Frey C. B., Osborne M. A. The future of employment: how susceptible are jobs to computerisation?, Technological Forecasting and Social Change.
(2017)
Job title Probability
Medical and Clinical Laboratory Technicians 47%
Epidemiologists 20%
Pharmacists 1.2%
Physicians and Surgeons 0.42%
Will Robots Take My Job?
Frey C. B., Osborne M. A. The future of employment: how susceptible are jobs to computerisation?, Technological Forecasting and Social Change.
(2017)
Das Ende