Artificial Intelligence as a

Disruptor

What’s coming and how AI can Boost

The Value of Lab Testing

Ajit Singh, Ph.D.

Partner, Artiman Ventures

Professor, School of Medicine

Stanford University

Executive War College

New Orleans, May 2nd 2018

five

vignettes

1 what can we learn from nature

2

myth vs reality: what is feasible today3

evolution of AI and transdisciplinarity

have you been stuck behind a Google car4

AI in medicine: when will the future arrive5

1 what can we learn from nature

myth vs reality: what is feasible today

evolution of AI and transdisciplinarity

have you been stuck behind a Google car

AI in medicine: when will the future arrive

2

3

4

5

lets take a short

journey

through a place of immense

diversity

a rich

diversityof life

where?

galapagos

why

right

temperature

1

good

mobility

2

natural mixing of

diversity

3

coral reefs

connectionsare made

failuresare discarded

quickly

nature’s

innovationplatform

diversity

human-made

innovationplatform

trans

disciplinarity

1

2

3

4

5

what can we learn from nature

myth vs reality: what is feasible today

evolution of AI and transdisciplinarity

have you been stuck behind a Google car

AI in medicine: when will the future arrive

Turing, A.M. (1950), Computing machinery and intelligence, Mind, Vol. 59, pp. 433-460

1950the Turing test

1951First chess-playing program developed by Dietrich Prinz at the University of Manchester. It ran on the Ferranti Mark I.

1955Allen Newell and Herbert Simon created the Logic Theorist that proved 38 of the first 52 theorems in Principia Mathematica

1956The term “Artificial Intelligence" was adopted at the Dartmouth Conference

implementationstwo prevailing

of artificial intelligence

algorithmssymbolic implementation of AI:

that manipulate symbols that represent concepts

(knowledge is hand-coded)

(also called expert systems)

1.

neural networksconnectionist implementation of AI

(knowledge is machine-learnt)

2.

Academic Disciplines relevant to AI.

Philosophy Logic, reasoning, foundations of learning, language, rationality.

Mathematics Algorithms, computation, (un)decidability, (in)tractability, probability.

Economics Utility, Decision theory

Neuroscience Neurons as information processing units.

Psychology How do people behave, perceive, process

Cognitive Science Knowledge Representation

Computer Engg. Computing, Storage, Communication

Control Systems Optimization of objective functions over time

Linguistics Knowledge representation, grammar

trans

disciplinarity

and…

data

(lots of it)

1

2

3

4

5

what can we learn from nature

myth vs reality: what is feasible today

evolution of AI and transdisciplinarity

have you been stuck behind a Google car

AI in medicine: when will the future arrive

questions let’s answer some illustrative

(these are illustrative, and not comprehensive)

human braincan we build hardware as complex as the

Q

brain10 12 neurons, 10 14 synapses, 10 -3 seconds cycle time

computers106 transistors per CPU, 103 – 104 CPUs, 10 9 bits of RAM, 10 - 8

seconds cycle time

YES computer systems with as many “neurons” as our brain, soon.

NO computer systems with interconnectivity of the brain any time soon

BUT building hardware will not achieve a computer behave like a brain!

recognize speechcan computer systems

Q

large vocabularies

speech has unclear word-boundaries but clear phoneme-boundaries

background noise, other speakers, accents, colds

CONTEXT plays a very important role

(“I would like some dream and sugar in my coffee”)

(“olive oil” is made from olives. “baby oil” is made for babies)

(“time flies like an arrow”)

YES CAN recognize individual words from small vocabulary (99% accuracy)

NO CANNOT “understand” speech (60% accuracy even in defined domains)

BUT building context in constrained domains will be possible in near future

see and perceivecan computer systems

Q

pattern recognition evolved over millions of years

vast variations in lighting conditions, occlusions, unknown objects

scene understanding evolved over millions of years

CONTEXT plays a very important role

YES to some kinds of objects in constrained environments (face recognition)

NO to general scene understanding in unconstrained environments

BUT solving this problem is central to building intelligent systems

1

2

3

4

5

what can we learn from nature

myth vs reality: what is feasible today

evolution of AI and transdisciplinarity

have you been stuck behind a Google car

AI in medicine: when will the future arrive

2 million milesand sensor data (camera, lidar, etc.) of

of Google caronly to reach the current capability

(the one you would not like to be stuck behind)

30 million milesto reach human-like capability

it will take sensor data from

30,000 milesthat human drivers are able to achieve in

why?

50+ million yearshumans are able to apply

of learning in pattern-matching

(that’s the power of evolution at work)

1

2

3

4

5

what can we learn from nature

myth vs reality: what is feasible today

evolution of AI and transdisciplinarity

have you been stuck behind a Google car

AI in medicine: when will the future arrive

breast cancerdiagnosis and therapy selection

let’s extrapolate the self-driving car learning to

correlated datawill we need

how many patients’ / healthy people’s

seven billion

(that’s the entire human population of planet earth)

great expectationsthis is a case of

(great, but unrealistic)

more importantly

replicatinghuman knowledge

simply

bad ideaby learning from humans is a

succeedwatson WILL

1 Optellum optellum.com Cancer diagnostics with AI and Big data

2 Quantitative Insights

quantinsights.com Machine learning based Computer aided diagnosis of breast cancer

3 Artificial Intelligence in Medicine

aim.ca AI based Software solution for cancer surveillance, prevention and research

4 GliaLab glialab.com Artificial Intelligence based health tech company

5 Magentiq Eye magentiq.com Computer vision technology in endoscopic procedures

6 Imagia Cybernetics imagia.com Medical image analysis using artificial intelligence for detecting cancer

7 PathAI pathai.com AI based solutions for clinical diagnosis

8 RadSupport radsupport.io Deep learning for mammography image analysis

9 Exact Imaging imagistxprostate.com

Prostate cancer imaging

10 Notable Labs notablelabs.com Precision medicine and clinical decision support solutions for Brain cancer

11 Freenome freenome.com Deep learning platform for detecting circulating cancer-related markers

12 Smart Health Care smarthealthcare.se Deep learning algorithms for cancer diagnostics.

13 LPixel lpixel.net Image analysis tools using artificial intelligence

14 ClearView Diagnostic

clearviewdiagnosticsinc.com

Computer-aided detection and diagnosis algorithms for breast cancer detection.

15 iSonoHealth isonohealth.com Self-monitoring Solution for Early Breast Cancer Detection

16 VisExcell visexcell.com Breast cancer risk assessment using AI

17 MobileODT mobileodt.com Smartphone-based diagnostic tools for the screening of cervical cancer

18 Entopsis entopsis.com Universal diagnostic platform

19 HaploX haplox.com NGS-based liquid biopsy tests for precision medicine

20 KMD Biomarkers kmdbio.com Urine-based metabolomics assay for determining cancer progression

21 Immortagen immortagen.com AI-based NGS solutions for cancer diagnostics

22 Maxwell MRI maxwellmri.com Imaging software solutions for cancer diagnostics.

23 AlgoRhythm Diagnostics

algorhythmdiagnostics.com

AI-based analysis tools for radiology images

24 Inform Genomics informgenomics.net Predictive pharmacogenomic platform for Oncology

25 CureMatch curematch.com Matches cancer patients with optimal Rx combinations

26 INTIO intio.us Image analysis for Interventional Oncology

27 Bering beringresearch.com Provides an Artificial Intelligence (AI) platform to identify complex patients and prioritizes actionable interventions

28 Deontics deontics.com SaaS based personalized CDSS using artificial Intelligence

29 Tempus tempus.com Oncology platform for sequencing, analytics and informatics

30 Avatar DSS avatardss.com Precision treatment support for cancer patients

31 Intervention Insights

interventioninsights.com

Evidence-based decisions support tool for molecular oncology

32 Syapse syapse.com Molecular profiling platform for diagnosing and treating patients

33 Oncora Medical oncoramedical.com Decision support tool for Radiation Oncologists

34 DiaScan diascan.co Software that analyzes CT scans for lung cancer using machine learning

35 LungDirect lungdirect.com LungDirect is Matrix Analytics’ end-to-end software suite that facilitates lung cancer screening data submission and optimizes patient care.

36 Medial EarlySign earlysign.com Develops a machine learning based decision support tool which enables personal and outcome-based interpretation of medical data.

37 N-of-One n-of-one.com Molecular profiling and analysis for hospitals

38 Feedback fbk.com Software solutions and workflows for medical image analysis

39 Hexalotus hexalotus.com 3D Medical Image Processing

40 Signifikance signifikance.com Application of genetic discoveries in clinical practice to enable Precision Medicine

41 Kuveda kuveda.com Provider of SaaS tools for analysis of cancer patients molecular profiles,

42 Turbine turbine.ai Design effective cancer combination therapies using artificial intelligence

43 Medint medint.io Medical Intelligence & personalized data platform to support medical decisons

44 Percans Oncology zkbymed.com Personalized treatment planning and services for cancer patients

45 Aindra aindra.in Developer of handheld devices with technology to detect and identify people

landscape of 40+ startups in pathology

modeling and capturing

EXISTINGknowledge and

making it available

modeling and learning

NET NEWknowledge to

improve human performance

dichotomy

modeling and capturing

EXISTINGknowledge and

making it available

successesarrhythmia recognition from electrocardiograms

coronary heart disease risk group detection

monitoring prescription of restricted use antibiotics

early melanoma diagnosis

breast cancer diagnosis

modeling and learning

NET NEWknowledge to

improve human performance

CELLWORKS

oncology therapy selection

GENXSYS

decision support for GP

SECONDOPINIONS.COM

radiology second opinion

promising

near termpredicting the

from?learning

1.

2.

3.

4.

5.

long termpredicting the

the future of the patient

Sample Market Signals

Networks & Sensors

Wearables

Learning System

Robotics

Sample Use Cases

Drivers of Disruption

Deloitte Cognitive Engagement – designed to boost patient involvement in care and expand the type of alerts and interactivity

New Ways to Engage

Tyto Care – handheld device that patients can use to self-examine their mouth, throat, eyes, heart, lungs, skin, and temperature

Tools for Self-Service

Ginger.io – aggregates cellphone data to monitor patient’ mental health and alert caregivers when symptoms are problematic

The Quantified Self

the future of care delivery

Sample Market Signals

Healogram – Mobile platform that helps providers remotely monitor patients post-surgical procedure

Where Care is Delivered

Retina Selfie – Retina self-imaging allows patients to monitor for diseases like multiple sclerosis and detect early warning signs

When Care is Delivered

Camera resolution

Robotics and NLP

Augmented Reality

Learning Systems

iDAvatars – Virtual avatar, Sophie, uses artificial intelligence and natural language processing to remotely monitor patients

Who Care is Delivered by

Sample Use Cases

Drivers of Disruption

the future of healthcare operations

Robotics

Learning Systems

Analytics

Communication Speed

Sample Use Cases

Aethon TUG Robots –Smart, autonomous robots substitute for the labor needed to transport materials & clinical supplies

Improved Productivity

Care at Hand – Helps to prevent readmissions by deploying nursing staff skills to maximum efficiency

Efficient Administration

Evena – Technician glasses provide high-definition, real-time images of vascular anatomy to enable fast, precise IV access

Workforce Augmentation

Drivers of Disruption Sample Market Signals

the future of precision medicine

Sample Market Signals

Genomics

Personalized Medicine

Nanotechnology

Sample Use Cases

Drivers of Disruption

LiverChip – Dynamic 3-D cell culture platform can exactly mimic the architecture and physiology of the human liver

New Treatment Methods

Human Longevity Inc. –building the world’s most comprehensive database on human genotypes

Preventative Measures

Wyss Institute –Harvard scientists built a nano-robot from designer DNA to deliver drug dosages to specific cell types

Increased Precision

the labwhat does it mean for

1. digitizing is key. start now

2. indexing is key. start now

3. storing correlated clinical data is key

4. start a pilot – coding, for example

5. start a pilot – chat-bot for counseling

the differences between us and them

emotion understanding consciousness

creativity

A.I. is the discipline of how to make computers do things at which, at the moment, people are better.

www.artiman.com