ICCES'2016 BIG DATA IN HEALTHCARE AND SOCIAL SCIENCES

Big Data in Healthcare and Social Sciences

VICTORIA LÓPEZ

UNIVERSIDAD COMPLUTENSE DE MADRID

Barcelona, Spain, 23-27 July- 2016 1

ICCES’2016International Conference of Computing for Engineering and Sciences

Outline

Healthcare and Social Sciences

Information Privacy

Some projects (as examples)◦ Bronchoopulmonary Dysplaxia

◦ Bipolar disorder

◦ Intelligent Integration of COhorts for a better life of DEMEntia patiens

◦ WAP Madrid

◦ Asperger disorder

The future is coming in 5 years…


Healthcare and Social Sciences Everybody, ….. Everybody … is sensible about healthcare.

No discusion about investing money/time/efforts

Clear goals for projects

Prevention vs. Curation (here the money is first)

Personal health: people are able to check their own rates

Healthcare becames a social issue


Individual knowledge

Social contributions

Colective knowledge

Social Development

Less effort

More improvements

Healthcare and Social Sciences


Individual knowledge

Social contributions

Colective knowledge

Social Development

Less effort

More improvements

Solutions come from predictive analytics

Predictive modeling

Machine learning

Data mining

GOAL: PREVENTION

Heathcare and Big DataIntelligent Data Analytics

Predictive analysis

Clustering

Pattern discovery

Visualization

FINE, www.finenet.nl


Problem formulation – data exploring – hypothesis formulation – working with data – experimentation – results – iteration

https://es.coursera.org/course/patterndiscovery

HealthCare and Big DataMost of problems in healthcare are big data issues.

About volume

◦ Nowadays we can collect data all over the world

◦ We are being monitoring! … all the time!

◦ -Accelerometers

◦ -Smartphones


Heathcare and Big DataMost of problems in healthcare are big data issue

About velocity◦ We need to know the crisis is coming in advance (asap)

◦ Real time must work as real time in real life

About variety◦ Data is unstructured and diverse

◦ Data pre-processing


Heathcare and Big DataMost of problems in healthcare are big data issues.

About veracity◦ Accuracity is a due!

◦ Not only money but also lifes

◦ Data cleaning and integration

◦ Noise and outlliers must be out of the sample


Information privacyRelation between:

Data collection –

Data dissemination –

Technology –

Legality –

Public expectation of privacy –


Information privacyThe challenge of data privacy is tu utilize data while protecting individual’s privacy preferences and their personally identifiable information

- computer security

- data security

- information security

Privacy becomes a big deal when health personal data is involved.


Information privacyTake into account:

Where storing data (cloud, inHouse, hybrid)

Who is allowed to see the data

How the data can be accessed

Is our project under the law?

New techniques: ◦ Data Anonymization ◦ Cryptography ◦ Disjoin private – public data


Information privacyData Anonymization

- Encrypting all or part of the data

- Removing sensible data

Personally identifiable information from data sets

Technology that converts clear text data into a nonhuman readable and irreversible form (no de-anonymization)


Some projects

◦ Bronchoopulmonary Dysplaxia

◦ Bipolar disorder

◦ Intelligent Integration of COhorts for a better life of DEMEntia patiens

◦ Wap Madrid

◦ Asperger disorder


BRONCHOPULMONARY DYSPLASIA PULMESCELL & PULMESGEN: GENETIC AND MOLECULAR BIOMARKERS PREDINCTING BRONCHOPULMONARY DYSPLASIA AND THE INDIVIDUAL RESPONSE TO MESENCHYMAL STEM CELL THERAPY


BRONCHOPULMONARY DYSPLASIA

INGEMM Pablo Lapunzina

INSTITUTE GENETICS HURYCJavier Moreno

STEM CELL PRODUCTIONManuel Ramirez Orellana

Modelos Animales Javier Garcia Castro

La Fe HospitalIP: Max Vento

La Paz HospitalIP: Paloma LópezD Elorza, C labrandero y Marta C.

Clinico HospitalIP: Luis arruza Santiago rueda y Cristina Glez Menchen

Vall d Hebron HospitalIP: Felix castilloAntonio Moreno Galdo (neumo) y Anna sabaté (cardio)

H.U. RAMON Y CAJAL IP: M. Jesús del CerroMaria Álvarez, Cristina Sanchez, E. Garrido

BIG DATA. Grupo GTeC - GRASIA Informática ComplutenseIP: Victoria Lópezy Guadalupe Miñana

Biomarkers

IP: Laura Moreno

Jane Mitchell,

Francisco Vizcaino

COST BENEFIT ANALYSISCSIAT IP: FJ Diaz UNED

CHUAC Hospital (A Coruña)

IP: Alejandro avilaC Blanco


BIPOLAR DISORDERCAD prediction system for bipolar disorder, a complex mental disorder in which the core feature is disturbance in mood, ranging from extreme elation (mania) to severe depression, accompanied by disturbances in thinking and behaviour.

2% of the world’s population. The disease has substantial consequences both for the individual and for health care spending.

The World Health Organization has identified BD as the sixth leading cause of disability-adjusted life years in the world. In 2009, the direct and indirect costs of BD were estimated to be US$151 billion. In the UK, the estimated national cost of bipolar disorder was £4.59 billion per year. Hospitalisation during acute episodes costs £69 million per year.

Biomedical informatics methods are needed to process data and form recommendations and/or predictions to assist decision makers in the form of computer-aided decision (CAD) support.


BIPOLAR DISORDER

Victoria López @victoriadematesBarcelona, Spain, 23-27 July- 2016 19

BIPOLAR DISORDER

Table: Patient features and types.


BIPOLAR DISORDERFigure 1. Hybrid Cloud-inHouse storing and computing


BIPOLAR DISORDER - team

1 PhD student, 1 Master student, 3 CS students, 3 senior researchers


H2020: I2-CODEME (Intelligent Integration of COhorts for a better life of DEMEntia patiens)


I2-CODEME consortium will provide a set of cohorts related with dementia and other neurodegenerative diseases that in particular will improve quality of life of patients by establishing home treatment protocols and it is expected that will decrease by around 20% the costs associated to treatments from the patient point of view.

I2-CODEMEEcosystem

Health&SocialCare

PolicyMakers

Pa ents&

Families

Figure 1. I2-CODEME Ecosystem Actors



As a result of the methodology applied, I2-CODEME will establish a set of KPIs (key performance indicators) from different perspectives (medical, healthcare, social care, policies).



Cost associated to early detection of dementia patients



Relationship between different machine learning frameworks



A platform on Open Data. Getting value from healthcare data.

WAP MADRID. WALKING PEOPLE.


Asperger syndromeAsperger syndrome (AS) is a developmental disorder characterized by significant difficulties in social interaction and nonverbal communication, along with restricted and repetitive patterns of behavior and interests. It is an autism spectrum disorder (ASD) and differs from other disorders by relatively normal language and intelligence.


Social Big Data


http://socialbigdata.transyt-projects.com/

http://socialbigdata.transyt-projects.com/

Big Data in Healthcare and Social Sciences

VICTORIA LÓPEZ

UNIVERSIDAD COMPLUTENSE DE MADRID


ICCES'2016 BIG DATA IN HEALTHCARE AND SOCIAL SCIENCES

Technology

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