Linguistic processing and classification of semi structured bibliographic data on complementary medicine.

Area of Science:

• Oncology
• Medical Informatics
• Complementary Medicine

Background:

• Cancer patients increasingly seek complementary and alternative therapies and medicines (CAM).
• Physicians require tools to access scientific publications on CAM, especially those outside major databases like MEDLINE.
• Existing resources may not comprehensively cover the growing body of CAM research.

Purpose of the Study:

• To introduce CAMbase, a novel XML-based bibliographical database for CAM research.
• To provide a user-friendly tool for physicians to obtain an overview of CAM scientific publications.
• To address the need for accessible information on CAM, particularly for oncology.

Main Methods:

• Development of CAMbase, an XML-based bibliographical database.
• Implementation of a custom front-end search engine with semantic analysis capabilities.
• Focus on indexing CAM literature not typically found in common bibliographic databases.

Main Results:

• CAMbase offers a free, online resource for CAM information (www.cambase.de).
• The search engine facilitates quick retrieval of relevant information through semantic analysis.
• The database provides statistics on search terms related to complementary therapies in oncology.

Conclusions:

• CAMbase serves as a valuable, free resource for accessing CAM literature.
• The database's semantic search enhances information retrieval for healthcare professionals.
• CAMbase supports informed decision-making regarding complementary therapies in cancer care.