Rasheed Rabbi

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Ontology – Supported Machine Learning and Decision Support in Biomedicine Alexey Tsymbal Sonja Zillner Martin Huber. Rasheed Rabbi. Presentation Outline. Research Goal Used example or case study Key Idea and Key words Health Care knowledge repository Questions. Research Goal. - PowerPoint PPT Presentation

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Rasheed Rabbi

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Presentation OutlineResearch Goal

Used example or case study

Key Idea and Key words

Health Care knowledge repository

Questions

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Research Goal

How ontology and Machine Learning can help extracting useful knowledge

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Case Study:Context: Health-e-child participants in 2006Source: biomedical information from

genetic clinical epidemiological

Goal: improve children disease prevention, screening, early diagnosis therapy and follow up of pediatric diseases

Methodology: Large Data Input Complex

pattern recog

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Machine Learning

Case Study: Diseases of 3 categories:

pediatric heart disease inflammatory disease brain tumors

Pediatric Heart Disease Atrial Septal Defect (ASD)

Hole in Atrial septum Treatment needs to happen from 4-6 years of ageThe prognosis of ASD depends on heterogeneous

feature of clinical data, genetic data, ECG and imaging data

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Case Study

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Key Concepts: Ontology:

Philosophy to describe the nature, categories and the relationship objects

Feature Ontology: Reflects both the semantic

and linguistic neighborhoods of a particular entity.

Constitutes a rich representation of an entity

Hierarchical structure in tree graph where N is the node, l is the level and w is the weight.

Ontology Ontology feature 7

Health Care knowledge repository

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Questions

Any Questions?

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Rasheed Rabbi

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OutlineIntroduction to mobile rehabilitation

application for remote monitoring PHM (Personal Health Monitor)Scenario Interface Remote Sharing

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Personal Health Monitor Ambulatory monitoringMultiple SensorsPersonalization Instant Feedback Software running locally on the

phoneArrhythmia Detection Reminders and logsCommunication Remote Monitoring via Health

Care Data server

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ScenarioJack walks 6 minutes to determine:

RPE O2 saturation

Can be monitored more than twice a week through his cell phone which has pairs of Bluetooth sensors. He wears the heart monitor and use the mobile monitoring

application during exercise It allows him to be familiar with the application while being

supervised After 2 weeks, he has gained enough confidence to do the

exercise in local gym using mobile rehabilitation appHe synchronize data every week with health center

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User InterfaceThree parts:

1. Live data 2. Configuration3. Rehabilitation

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Remote MonitoringUser can monitor on their own Their data can be uploaded to a remote site

Synchronization between the mobile phone and website happens using 3G.

Website is secure and accessible to patient and health professionals

Alert generate measurements are over threshold

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Questions

Any Questions?

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