Content-Mining for Clinical TrialsPeter Murray-Rust

contentmine.orgCochrane UK, Oxford, 2015-03-16

• OPEN Platform for Machines+humansto automatically “read” the trials literature

• Grow communities and give everyonethe tools and know-how to mine trials

• 09:30 - Introductions10:00 - Overview of ContentMine10:30 - Discussion: why might content mining clinical trials be useful?11:00 - Tea/coffee break11:15 - Discussion: current tools and what is needed12:00 - Discussion: imagining the clinical trials mining pipeline12:30 - Lunch13:30 - Demo and introduction to software14:30 - Technical session 1 (hands-on content mining)15:30 - Tea/coffee break15:45 - Technical session 2 (hands-on content mining)17:00 - Event close

Background for Today• Contentmine aims to make large areas of scientific fact OPEN (100

million facts/year)• We’re working with WellcomeTrust, Europe PubMedCentral, etc.• A politically “hot” area (Hargreaves legislation, EU activity)• A week ago WellcomeTrust workshop on TDM and Neuroscience;

“rough consensus” on what was needed.• In the last few days we’ve prototyped what we think is a good

starting point…• NOTE: The software is very “bleeding edge”! Please treat in a spirit

of adventure!!

• Vision/enthusiasm from Amy Price, Anna Noel-Storr, Emily Sena(E’burgh) and yourselves!

Questions we could tackle

• How to we find (mentions of) clinical trials?

• Is a document a (clinical) trial?

• What is the subject of the trial?

• What is the methodology used?

• Does the design and practice conform to CONSORT?

• What are the outcomes?

• Can we extract specific re-usable information?

• Who are involved? (researchers, sponsors, patients?)

• Has a proposed trial been completed and reported?

Afternoon session

• Work in groups; mixture of skills and experience

• Take different sections of CONSORT

• Scrape articles from trialsjournal.com

• Explore word frequency – create your own lists of frequent words

• Design regexes to extract CONSORT 8a->11

The Right to Read is the Right to Mine

http://contentmine.org

https://en.wikipedia.org/wiki/Irrigation#mediaviewer/File:Pump-enabled_Riverside_Irrigation_in_Comilla,_Bangladesh,_25_April_2014.jpg CC BY-SA 3.0

Daily Stream of 100,000 Open Facts

Twitter?Indexed by CAT

What is “Content”?

http://www.plosone.org/article/fetchObject.action?uri=info:doi/10.1371/journal.pone.0111303&representation=PDF CC-BY

SECTIONS

MAPS

TABLES

CHEMISTRYTEXT

MATH

contentmine.org tackles these

What is “Content”?

Machine-Human symbioses

• Wikipedia

• Open StreetMap

• Google

We aim to make it trivial for a human+machineto mine the scientific literature.

By building Communities

ContentMine Workshops and Hackdays

Open Science Brazil, 2014-08

Easily distributed software

Get started in 30 mins

Build application in a morning

Start simple: bagOfWords, Stemming, Regex, templates

Oxford 2013

Berlin 2014

Delhi 2014

Jenny Molloy with mascot AMI

Workshops (1-hour -> full day or more)

2014-May->Nov• Budapest/Shuttleworth• Leicester Univ• Electronic Theses and Dissertations• Austrian Science Fund AT• OKFest DE• Eur. Bioinformatics Institute• Open Science Rio de Janeiro BR• Sci DataCon , Delhi IN• Univ of Chicago US• OpenCon 2014, Wash DC. US• JISC , London

Upcoming• LIBER • Cochrane• BL• Wellcome Trust (April)• WHO

Collaborators

• Wikimedia/Wikidata

• Mozilla

• Open Knowledge

• LIBER (European Research Libraries)

• British Library

• Wellcome Trust

• EBI (Eur. Bioinf. Inst.)

• JISC

• Open Access Button

• SPARC

• Creative Commons

• CORE

• EuropePubmedCentral

• CRAWL the web for scientific documents(articles, grey literature, repositories)• quickSCRAPE pages (text, graphics, images, data)• NORMA-lize page to semantic form

…Open semantic science …• MINE pages with your methods and tools (AMI)

• CAT-alogue results in searchable index• Automate daily process (CANARY)

contentmine.org Infrastructure

quickscrapeCrawlFeed

Norma Index &Transform

PDF

XML

URL

DOI

Scientificliterature

Repositories DOC

CSV

sHTML

Plugins

Regex

SequencesSpecies

Bespoke

Scrapers

XPathPer-Journal

Taggers

Per- Journal

MetadataChemistry

Phylogenetics Farming

AMI

BadHTML

OCR

Diagrams

Open NORMA-lized Scientific Literature + Facts

CANARY pipeline

CAT-alogue index

https://commons.wikimedia.org/wiki/File:Flickr_-_DVIDSHUB_-_RSP_Warrior_Challenge_Prepares_Soldiers_Mentally,_Physically_%281%29.jpg

CRAWLing the Literature

NO Central Table of Contents

Massive technical, political, legal opposition

Little interest from Academia

Tedious

Few general tools

The Right to Read is The Right To Mine

PMR in 2012: http://blog.okfn.org/2012/06/01/the-right-to-read-is-the-right-to-mine/

SCRAPE

https://en.wikipedia.org/wiki/Gleaning#mediaviewer/File:Millet_Gleaners.jpg PublicDomain

PDF

HTML

XML quickscrape*

*Scrapers created by Richard Smith-Unna +

Community

HTMLPDFXMLPNGSVGCSVDOCLaTeXCIF…

Non-standard per-publisher site

https://en.wikipedia.org/wiki/W._Heath_Robinson#mediaviewer/File:Robinson%28WH%29-%28%27Uncle_Lubin%27%29.jpg PublicDomain

NORMA-lization of Scientific Literature

PDFs, Broken HTMLPNGs for Math, etc.

NORMA

UnicodeDiacriticsWell-formedSectionedTaggedSVG diagrams

AMI-plugins

• BagOfWords, Stemming and Regular Expressions• Species• Biological Sequences• Chemical compounds & reactions

• Farming * (Rory Aaronson)

• Crystallography * (Saulius Grazulis, COD)• Clinical Trials * (Amy Price)

• Phylogenetics * (Ross Mounce)

• Phytochemistry * (Chris Steinbeck, PMR)

* subcommunities

Text-based plugins

• Bag of words (https://en.wikipedia.org/wiki/Bag-of-words_model)

• https://en.wikipedia.org/wiki/Tf%E2%80%93idf

(Term-frequency, inverse document frequency)

• Templates and regexes (regular expressions).

“Bag of Words”

Three fulltext articles from trialsjournal.com

Facts Marked by “non-scientists” in ContentMine workshops

With Wikipedia everyone can be a scientist

“nuggets” in a scientific paper

quantity

units

Value ranges

Humans aren’t designed to mine this … chemical

project places

Advanced Plugins

http://chemicaltagger.ch.cam.ac.uk/

• Typical

Typical chemical synthesis

Open Content Mining of FACTs

Machines can interpret chemical reactions

We have done 500,000 patents. There are > 3,000,000 reactions/year. Added value > 1B Eur.

UNITS

TICKS

QUANTITYSCALE

TITLES

DATA!!2000+ points

Dumb PDF

CSV

SemanticSpectrum

2nd Derivative

Smoothing Gaussian Filter

Automaticextraction

AMI https://bitbucket.org/petermr/xhtml2stm/wiki/Home

Example reaction scheme, taken from MDPI Metabolites 2012, 2, 100-133; page 8, CC-BY:

AMI reads the complete diagram, recognizes the paths and generates the molecules. Then she creates a stop-fram animation showing how the 12 reactions lead into each other

CLICK HERE FOR ANIMATION

(may be browser dependent)

https://blogs.ch.cam.ac.uk/pmr/2014/06/25/content-mining-we-can-now-mine-images-of-phylogenetic-trees-and-more/ for story of extraction

Thinning Topology

Serialization

Newick

Phytochemistry extraction

O. dayi

“volatile composition of “

A.sibeiri

A. judaica

Displayed by CAT (CottageLabs)

contentmine.org proposed Services

• Workshops

• Repository indexing

• Funder Compliance

• Publication enhancement

• Extraction of scientific data

contentmine.org team