Homer R. Warner, Dean K. Sorenson, Omar Bouhaddou

Knowledge Engineering in Health Informatics (eBook, PDF)

• Format: PDF

Produktbeschreibung

The "information explosion" has made it impossible for physicians to consistently make optimal decisions. Thus, medical expert systems are now available to support physicians in providing the best possible healthcare to every patient. This is a guide to such systems, presenting the core material for courses such as Medical Knowledge Engineering and Expert System Development.

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Produktdetails

• Verlag: Springer US
• Seitenzahl: 265
• Erscheinungstermin: 6. Dezember 2012
• Englisch
• ISBN-13: 9781461218227
• Artikelnr.: 44063946

Inhaltsangabe

1 Background and Legacy.- Overview.- Knowledge Representation and Computation Methodologies.- 2 The Expert System Model.- to Modeling.- Choosing a System to Model.- Choosing a Model.- 3 Iliad: The Model Used for This Text.- The Frame Concept.- The Probabilistic Model: Dealing with Uncertainty.- Probabilistic Information.- Heuristics That Improve the Model.- 4 The Data Dictionary: Limiting the Domain of the Model.- Organization of the Dictionary.- Context Versus Concept.- Hierarchical Relationships.- Granularity of the Dictionary.- Modifying the Dictionary.- Knowledge Contained in the Dictionary.- Inferencing from the Hierarchy.- Word Relations.- Data Relations.- 5 The Knowledge Engineering Process.- How to Structure/Model the Knowledge.- The Overall Process.- Knowledge Sources: Advantages and Limitations of Each.- Which Findings to Include in a Frame.- Probabilistic and Deterministic Logic.- Reasons to Cluster.- Types of Clusters.- Frames That Return a Value.- Estimating Probabilities.- Testing Frames in Isolation.- Sources of Error.- Tools to Facilitate the Knowledge Engineering Process.- Combining Frames into a Working System.- 6 Evaluation of the Model.- Testing and Refining the Compiled Knowledge.- Appropriateness of Decisions Based on Data Entered by Experts.- Testing with Data Newly Entered from Patient Charts.- Testing with Cases Stored Earlier.- Modifying Source Frames As Required: The Iterative Process.- 7 Applications of the Model.- Modes of Use.- The User Interface.- Minimal Diagnosis.- Bayes Calculator.- Interfaces to Other Knowledge.- Compromises.- 8 Lessons Learned.- Teaching Medical Clerks, Physician Assistants, and Other Trainees.- As a Tool for Preauthorization.- As a Screening Tool for Quality Improvement.- Commercial Users of Iliad.- 9 Knowledge Engineering Tools.- Knowledge Acquisition.- Structuring and Coding the Knowledge.- Testing the Knowledge Base.- Summary.- 10 Example Knowledge Bases.- The Knowledge Engineering Class.- Medical and Pediatric HouseCall.- Symptom Analysis.- Deriving HouseCall from Iliad.- Knowledge Engineering for HouseCall.- 11 Future Challenges.- Links to Patient Data: Client Server/Version of Iliad.- Future Directions.- References.- Appendices.- 1 Example Hierarchies of Top-Level Diseases (Final Diagnoses) in Various Medical Specialties.- 2 Approximate Estimated Prevalences for Selected Top-Level Diseases in a Family Practice Setting, Categorized by Specialty.- 3 Using the Iliad KE Tool.- 4 Some Example "Domain-Specific" Symptom Lists.- 5 Example Data Relations.- 6 Example Word Relations.