1. Semantic Medicine
sedic

2. Project Objectives
 Provide assistance in choosing a proper tea based on medical history and
a presumptive diagnosis made by system upon a set of symptoms
 Provide assistance in following a cure, possible as an adjuvant treatment for
a disease.
 Automatic exclusion from recommendations of certain teas that contain
substances to which the patient is allergic or suffer from a disease in which
are not commended.
 Possibility to create a personal collection of teas, eventually with some
notes attached

3. Project Objectives
 Provide a SPARQL end-point for unlimited interaction with data
 Examples of utilization and a documentation will be provided
 Ex: SELECT ?plant
WHERE{{?plant <http://http://myschema.org/terms/cure>
<http://myschema.org/terms/symptoms/coldness> }
}
 Result: Tilia Tea known as : linden or basswood
Green Tea
Satureja hortensis knons as: Summer savory

4. Project Objectives
 Provide a REST service through which a user can perform various tasks .
 This provides the opportunity to integrate this system in other applications
 The REST service will be accessible via URL
 Ex. http://www.semanticmedicine.org/plants get all plants
 http://www.semanticmedicine.org/plants/Tilia get tilia details
 http://www.semnaticmedicinee.org/cure/cold get all plants that cure coldness
 http://www.semanticmedicine.org/disease/kidney_stone get adjuvant
treatment for kidney stone

5. Presumptive Diagnosis
 First step is to ask user to input some symptoms or diseases that is
suffering
 Based on this input:
 User can ask for tea to treat his symptoms
 User can ask for an adjuvant treatment for a suffering diseases

6. User input example
 Example of input:
 User suffers from a heart disease
 Is not allergic to any substance
 He wants a tea for his insomnia
 The result in this case will recommend:
 Matricaria chamomilla tea, also known as : chamomile, wild chamomile,
or scented mayweed
 Valeriana officinalis tea, also known as: garden valerian,
garden heliotrope, or all-heal

7. Reminder and cure schedule
 A user has the possibility to set a reminder that will help him in a cure
with tea.
 Ex: If he follows a cure with cherry tails for a kidney disease, he can
set a reminder that reminds him to drink his cherry tails tea.

8. Use case
 Note:
 User can ask for recommendations even if is not registered
 This use case doesn`t include SPARQL end-point or REST service utilization!

9. Data source
 Data will be collected using Apache Any23
 The main source will be represented by DBpedia
 Other sources will be used to collect additional information
 Some information will be added manually, if is not possible in
another way

10. Data storage
 Data will be storage as triples
 In this purpose will be using Jena TDB
 The final source will be represented by a union of graphs containing
common data. This process of union is automatically made by Jena

11. Example of data

12. Example of data

13. SPARQL end-point
 Example:
SELECT ?plant
WHERE{{?plant
<http://myschema.org/terms/cure>
<http://myschema.org/terms/symptoms/coldness> }
UNION {?plant
<http://myschema.org/terms/cure>
<http://myschema.org/terms/symptoms/insomnia>}
} ORDER BY ?plant
 Result: Tilia tea also known as : linden or basswood

14. SPARQL end-point
 Example:
SELECT ?plant
WHERE{ {?plant
<http://myschema.org/terms/cure>
<http://myschema.org/terms/symptoms/insomnia>}
MINUS {?plant
<http://myschema.org/terms/forbidden>
<http://myschema.org/terms/disease/high_blood_pressure>}
}
 Result:
 Matricaria chamomilla tea, also known as : chamomile, wild chamomile or scented mayweed
 Valeriana officinalis tea, also known as: garden valerian, garden heliotrope or all-heal
 Note: Recommendations will include Tilia (linden tea) due to high blood
pressure

15. Architecture overview
UI HTML5 (with RDFa) & JS & CSS3
REST service
Form Input interpreter
SPARQL endpoint
SPARQL Query builder & Parser
TDB Jena Triple store

16. Data navigation
 A visual navigation on data graph will be available with which users can
navigate through the plant, symptoms or diseases that are related
 Useful tools: Sgvizler library
 Similar with:
From: http://arborjs.org/

17. Conclusion
 At the end of the project:
 A user will be able to get useful information based on specific needs
 Will have the possibility to be assisted to follow a cure
 Possibility to interrogate data via a SPARQL end-point
 A REST service will be provided
 A visual exploration of data will be provided