big data analytics in healthcare: promise and potential for rare disease
DESCRIPTION
Presented by Chedy Raïssi, INRIA, France last 28 October 2015 in Bogor, IndonesiaTRANSCRIPT
10th CRISU-CUPT International Conference 29 October 2015
Big data analytics in healthcare:
promise and potential for rare disease
Chedy Raïssi, INRIA - France
29 October 2015 10th CRISU-CUPT International Conference
Context
29 October 2015 10th CRISU-CUPT International Conference
Context
29 October 2015 10th CRISU-CUPT International Conference
Experimental platforms
29 October 2015 10th CRISU-CUPT International Conference
Motivation
There is an increasing use of the Web in events of overall interest such as
politics, sports and health.
Smartphones and connected objects
are almost personal medical devices.
Use it to monitor heart rate, diet, exercises.
Technology will only get smarter.
What are the implications of this rise of digital technology in healthcare?
Relation to climate change?
Our goal: qualify, quantify, understand and summarize content being exchanged,
stored in various ways and evaluate the impact on specific healthcare events.
29 October 2015 10th CRISU-CUPT International Conference
Outline
Today: 2 case studies
Dengue
Web
Observator
y
Orphan
Disease
Analytics
Platform
29 October 2015 10th CRISU-CUPT International Conference
Background on Dengue
• Dengue: a mosquito-borne infection
-causes a severe flu-like illness
-sometimes a potentially lethal complication
-approximately 2 billion people at risk (> 100 countries), 50 million infections
• Outbreaks tend to occur every year during the rainy season
- but there is a large variation of the degree of the epidemic in areas with
similar rainfall
• Current strategies for prediction of dengue epidemics
-surveillance of insects
-outbreaks detection may take a few weeks
- loss of precious time to address the epidemic
29 October 2015 10th CRISU-CUPT International Conference
Dengue Web Observatory
Design and implement an active surveillance framework
-analyzes how social media reflects epidemics
-based on a combination of four dimensions
volume, location, time and public perception.
Predict?
Analyze dengue epidemics manifestations in Twitter for surveillance.
29 October 2015 10th CRISU-CUPT International Conference
Dengue Web Observatory
Methodology steps
• Content analysis (NLP)
• Correlation analysis
• Spatio-temporal analysis
• Surveillance
Determine the sentiment categories
• Personal experience: “You know I have had dengue?”
• Ironic/sarcastic tweets: “My life looks like a dengue-prone steady water”
• Opinion: “the campaign against dengue is cool”
• Resource: “Dengue virus type 4 in circulation”
• Marketing: “Everybody must fight dengue. Brazil relies on you”
29 October 2015 10th CRISU-CUPT International Conference
Dengue Web Observatory
Methodology steps
• Content analysis (NLP)
• Correlation analysis
• Spatio-temporal analysis
• Surveillance
29 October 2015 10th CRISU-CUPT International Conference
OrphaMine
A rare disease, also referred to as an orphan disease, is any disease that affects
a small percentage of the population.
« Rare diseases are rare, but rare disease patients are numerous »
-Estimation: 3 million patients in France
• The project is based on the analysis of the Orphanet ontology.
29 October 2015 10th CRISU-CUPT International Conference
OrphaMine
Simple and intuitive visualisation for each disease
29 October 2015 10th CRISU-CUPT International Conference
OrphaMine
Network visualisation and analysis
29 October 2015 10th CRISU-CUPT International Conference
OrphaMine
PubMed search
29 October 2015 10th CRISU-CUPT International Conference
OrphaMine
Differential diagnosis
• based on a log linear model
• takes into account medical observation of symptoms
29 October 2015 10th CRISU-CUPT International Conference
OrphaMine
10th CRISU-CUPT International Conference 29 October 2015
Terima Kasih, ขอบคุณครับ, Merci, ً شكرا