25min-oct2013

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Towards Patient-Specific Treatment:Medical Applications of Machine Learning

Russ GreinerAlberta Innovates Centre for Machine Learning

& Department of Computing Science

University of Alberta

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Personalized Medical Treatment Often, many treatment options for a disease

breast cancer, leukemia, Crohns disease,

Which is best for Patient#73?

Dunno.

Try the first, or

the one that works on previous patient, or

latest-&-greatest drug, or

Better: identify treatment best for specific patient

Not just Stage 4 melanoma but Stage 4 melanoma, 60yo male, BMI=20,

+ histology + genetics +

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Approach Requires knowing the connections:

Patient Features DiseaseX Patient Features Effectiveness of Treatment7

Unfortunately, NOT known

Fortunately, there is often data fromprevious patients (with known outcomes)

LEARN the connections from thathistorical data

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Supervised Learning Framework:

Learning a Classifier-catenin -catenin E-cadherin p120 age size pten recur?

m c n m c n m c n m c n

4 3 0 2 0 4 0 0 2 2 0 0 60 4 3 Y

: : : : : : : : : : : : : : : : : :

0 1 4 3 0 2 0 4 0 0 2 1 2 70 2 4 Y

1 4 3 0 2 0 4 0 0 2 1 2 0 62 6 1 N

: : : : : : : : : : : : : : : : : :

1 2 0 1 4 3 0 2 0 4 0 0 2 71 2 2 N

-catenin -catenin E-cadherin p120 age size pten

m c n m c n m c n m c n

0 1 4 3 0 2 0 4 0 0 2 1 2 70 2 4

Classifier

Learner

recur?

N

Novel patient

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Topics Seeking StudentsApplications

fMRI [functional Magnetic Resonance Imaging]

IDM [Intelligent Diabetes Management]

Cancer Heterogeneity[LDA?]

Predict Metabolites

Foundational

PSSP [Patient Specific Survival Prediction]

Experimental Design

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fMRI for

Psychiatric Disorders

Many psychiatric disorders look similar

depression and bipolar disorderoften have similar presentations

but different treatments

Variability in population of patients, with same disorder What works for one patient, might not work for another

Use fMRI (functional Magnetic Resonance Imaging) to distinguish disorders to better identify best treatment

Our results to date: Intl competition: Distinguish ADHD vs control: best performance, 2 pubs

Next step: First episode psychosis; Depression vs BiPolar;

w/ Dept of Psychiatry (M Brown, A Greenshaw, S Dursun, R Ramasubbu,)Skill: Imaging, Signal Processing + MachineLearning (Neurophysiology is useful)

BOLD

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Intelligent Diabetes Management Each patient with TypeI diabetes must

regulate his/her own insulin: Give self a dose of insulin (4x / day), based on

Current blood glucose level Anticipated carbohydrate consumption Stress

Dose is based on formula specific to patient varies over time

Diabetes MD can adjust formulabased on patients Diabetes Diary but only on visits every 3-6 months? none in 3rd word countries

Automate this policy adaption process Reinforcement Learning! w/ Alberta Diabetes Institute (E Ryan, P Senior, )

Skill: Reinforcement Learning, Implementation, (Endocrinology is useful)

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Cancer Heterogeneity Proper treatment depends on specific (sub)disease

Many diseases are mixtures of subtypes Single patient really has multiple subtypes

For each individual with BreastCancer Disease = mixture of Strains

Strain = distn over mutations

Challenge: Given set of patients, each with set of mutations

Compute set of (latent) strains,each w/ distn over mutations

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Topic Modeling

LDA Specific document

= mixture of Topics

Topic= distn over words

Specific patient= mixture of Strains

Strain= distn over mutations

LDA (Latent Dirichlet Allocation)

Given set of Documents,

Can learn

topics, and

associated distributions Then use this to characterize

new document

PatientPatient

Strains

Strain

Strain

Mutations

Mutation

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LDA for Cancer Heterogeneity Colleague in BC Cancer has ~2000

breast cancer samples including mutations for each

Learn strain model (using LDA?)

For new patient:

Given mutations, predict strain mixture

Later: consider EVOLUTION of cancersubtypes (within single patient)

Skill: Graphical models, (Oncology is useful)

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Predict Metabolites When you eat something

(food, drink, drug, ):Your body transforms it into products

metabolized into metabolites

The body then uses those metabolites

Food Producers / Drug companies / REALLYwant to understand this process!

What will DrugX metabolize into??

No one knows this now But

We have ~1000 [X, metabolites[X] ] pairs

Skill: Kernel Methods, (BioChemistry is useful)

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Topics Seeking StudentsApplications

fMRI [functional Magnetic Resonance Imaging] IDM [Intelligent Diabetes Management]

Cancer Heterogeneity [LDA?]

Predict Metabolites

Foundational


Experimental Design

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Stage 4 Stomach Cancer

Based on 128 patients

Median survival time:

11 months

80% confidenceinterval

10% to 90% 2 51 months

Based ONLY oncancer location/stage

11 months2 months

0.9

0.1

51 months

0.5

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Stomach Stage 4 Cancer

#1314 #1523

Cancer Type,

Stage

Stomach,

Stage4

Stomach,

Stage4

Predicted Survival Time 21[6.2 - 76]

2.2[0.8 4.8]

Median: 1180% CI: 2- 51

HGB 143 60

CREATININE_SERUM 108 305

ALBUMIN 43 35

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PSSP Status Survival Prediction Survival Analysis

Useful for predicting time to death for patient time to relapse for patient time to failure for machine part

time to re-injury for athlete

Extends Cox Regression, Kaplan Meier curve,Risk Assess, Involves ALL patient information, Deals effectively with censored data Is well calibrated: statistics mean something!

Website: http://pssp.srv.ualberta.ca/

Next steps:* Multiple time probes

* More robust* High dimensional data*

Skill: Foundational machine learning,

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Experimental Design Two standard treatments for Leukemia

Several tests available + 5 news ones Want a good policy:

OUR GOAL:

Part of national project,funded from Terry Fox Research Institute

Skill: Foundational machine learning,experimental design

Which tests to run, to best identify

which patient should get which treatment

Efficiently find this good policy:training using minimum #patients, #tests

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Other Tasks Application Pull

Metabolomic Tasks (small molecule) Brain Tumor Analysis

Microarray tasks [transplant, cancer, diseases]

Medical imaging histologically stained slides

Technology Push

large p, small n tasks

Microarray, SNP, MRI (brain tumor), fMRI

Covariate Shift

Explaining Gene Signature Anomaly

you tell me

30,000 Genes

3200Enzymes

2300Chemicals

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26

30,000

SNP Analysis

Microarray

Proteomics

Metabolomics

SubCell Location

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Collaborators

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ResultsGiven Predict

the subcell location of a BreastCancer

patients junctional proteins

her 5 year disease free survival

a subjects genetics[Single Nucleotide Polymorphisms]

whether she will develop breastcancer

the expression level of the genes in awomens breast cancer tumor biopsy

whether she is ER+ or ER-

a patients metabolic profile whether s/he will lose muscle mass(cachexia)

whether s/he should be screenedfor colon cancer

fMRI scan of subject whether subject has ADHD

whether subject has psychosis

MRI scan of brain tumor patient long vs short range survival

summary of Crohn patients gut flora 1 year relapse, or not

Pub?

y

y

s

y

y

y

s

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Recent Pubs.. all with studentsMultiple Pubs in PLoS One Nucleic Acids Research

Bioinformatics BMC Bioinformatics Metabolomics Frontiers in Systems Neuroscience

PLoS Biology Journal of Nutrition Theoretical Biology and Medical

Modelling Human Genetics Breast Cancer Research & Treatment Current Oncology Radiation Research Clinical Cancer Research Analytic Chemistry Journal of Chromatography B

as well as Computerized Medical

Imaging and Graphics

Medical Image Computingand Computer-AssistedIntervention (MICCAI)

NIPS ICML

AAAI

IJCAI

UAI EMBC

ISVC

See http://tinyurl.com/MedInfo-Papers

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Topics Seeking Students fMRI [functional Magnetic Resonance Imaging]

IDM [Intelligent Diabetes Management]

Cancer Heterogeneity

Predict Metabolites


Experimental Design

Imaging, Signal Processing + MachineLearning (Neurophysiology is useful)

Foundational machine learning, experimental design

Graphical Models, (Oncology is useful )

Reinforcement Learning, Implementation (Endocrinology is useful )

Foundational machine learning,

Useful, but NOT necessary

you can learn what you need!

Skill: Kernel Methods, (BioChemistry is useful)