New York USALondon UKMunich GermanyZug Switzerland

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)

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

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

215

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