BMI 210: Modeling Biomedical Systems

  1. What is a knowledge representation?
    • Represent information about the world for a computer to use to solve problems, I.e. diagnosing medical conditions.
    • Incorporates logic to enable reasoning by the computer
  2. Main approaches to knowledge representations:
    • 1. Logic Programming (First Order Logic aka FOL)
    • 2. Semantic Networks
    • 3. Frames (a type of semantic network)
    • 4. Rule-based systems
  3. Procedural knowledge representation
    • Knowledge is stored as program code
    • Usable only in a specialized problem-solving context
    • Highly efficient (in the correct context)
    • Used to execute functions that do things
    • Examples:
    •   Plan a route from Stanford → SFO
    •   Find all family members of Tiffany
  4. declarative knowledge representation
    • Knowledge stored as propositions that must be interpreted
    • Accessible for a variety of purposes
    • Relatively inefficient for problem-solving
    • Used to declare a certain logical statement is true or not
    • Or use to declare that two objects have a certain relationship
    • Examples:SFO is 30 miles from Stanford → distance(Stanford, SFO) = 30
    • Tiffany and Ben are siblings → siblings(Tiffany, Ben)
  5. Knowledge representations: expressivity
    you can say what you want to say
  6. Knowledge representations: soundness
    you will get all the right answers
  7. Knowledge representations: completeness
    you will get all the answers
  8. Knowledge representations: decidability
    you will get an answer
  9. Knowledge representations: 

    The trade-off between expressivity and decidability
    Fundamental tradeoff between being able to say what you would like to say about the world being modeled (expressivity) and knowing that inference is decidable and computationally efficient (tractability)
  10. The trade-off between expressivity and decidability: tables in a database
    • Not very expressive
    • Offer computationally tractable relational operations
    • Look up all males under 30 with disease X
  11. The trade-off between expressivity and decidability: sentences in first-order logic
    • Very expressive
    • Logical inference may be computationally intractable
    • Start with set of axioms and formulas that are true
    • Use modus ponens to make conclusions about other formula
    • Many formulas and variables can be expressive, but may be intractable to solve for all of the variables
    • Might be no solution, in which case the query is “undecidable”
  12. Order from least expressive to most expressive:
    a) frames
    b) description logic
    c) first order logic
    • 1) Frames
    • 2) Description logic
    • 3) first order logic
  13. True/False: Rule-based systems are a knowledge representation
  14. True/False: Rule-based systems are a problem solving method
  15. Rules in a rule-based system are of the form...
    if ... then ...
  16. What knowledge representation do we use backward/forward chaining on?
    rule-based systems
  17. What is backward chaining?
    • Goal-driven reasoning
    • Start with our final goal (e.g. Fritz is green)
    • Find rules with our goal as the consequent (then clause), use the antecedent (if clause) as our new goal
    • Repeat until we can prove the antecedent with our given truths
  18. Name a biomedical system that uses backward chaining.
    • MYCIN
    • Goal: find significant disease-causing organismsUses rules to available data
    • Once it finds such organisms, it attempts to select a therapy to treat the disease(s)
    • Designed as a consultant for physicians - given the ability to explain both its reasoning and its knowledge
  19. What is forward chaining?
    • Data-driven reasoning
    • Repeated application of modus ponens
    • Modus ponens
    • If conditional statement if p then q is accepted, and p holds, then the consequence q may be inferred
    • Search rules until we find one where the antecedent is true
  20. Name three problems with rule-based reasoning.
    • Rules offer much more flexibility in problem solving, but they do not encode inspectable models as frames do
    • Rules are hard for developers to maintain
    • No means to introspect the knowledge within the systems (rules)
    • Rule engine cannot scan through rules to adjust them, add rules, or delete rules
  21. Name three standard rule-based systems.
    • Arden Syntax
    • Health e-Decisions
    • MYCIN
  22. What is Arden syntax? What kind of system is it?
    • Markup language used for representing and sharing medical knowledge
    • Rule-based system
  23. The rules in Arden syntax are often forward or backward chaining?
    • Rules are often “data-driven” (aka forward-chaining)
    • Thus, when a physician enters new info about a patient, the system searches for rules that are relevant.
  24. Four functions for Arden syntax:
    • Alert: messages for dangerous situations
    • Medication interaction or dangerous lab result
    • Interpretation: a non-emergency messaged designed to supply supportive information such as an interpretation of liver function tests
    • Screen: message sent to clinical researchers when a patient meeting criteria for clinical trial or quality assurance concern are admitted to hospital
    • Management: messages used for administrative purposes such as managing bed assignments, same day admissions and discharges from hospital
  25. Name two use cases for Health e-Decisions
    • 1. Clinical decision support artifact sharing
    • 2. Clinical decision support guidance service
  26. What is Health e-Decisions:
    Clinical decision support for artifact sharing?
    • Answered the question: “How can I share a really good clinician decision support rule with someone else in an electronic format, so they can use the rule in their electronic health record?”
    • Focused on sharing three types of artifacts
    • Event-condition-action rules
    • Order sets
    • Document templates
  27. What is Health e-Decisions:
    Clinical decisions support guidance service?
    Answered the question: “How can I send important data to an up-to-date website or service that will give me advice about immunizations or other complex decisions?”
  28. Name a big criticism of rule-based systems in a clinical setting.
    • One big criticism of rule-based systems is that they fail to capture the complexities of a patient’s situation, which might include many (potentially conflicting) symptoms and other information that needs to be consolidated into a differential diagnosis. Some more advanced systems that used rules but accounted for more complexity include:
    • MYCIN: Accounted for lots of info about a patient via “Evidence Combination” and gave a differential of infectious diseases
  29. What does a frame-based system represent?
    Representation of classes, attributes, and values
  30. A frame-based system consists of templates to record values of properties of ______
  31. Frame-based systems are a hierarchy of ___ and ___
    nodes and relations
  32. Frame-based systems share a lot with traditional...
    object-oriented models
  33. Semantics of frame-based systems are based on...
    set theory
  34. Five advantages of frame-based systems:
    • Offer cognitive tractability
    • Class hierarchy organizes a flat knowledge base by introducing structure
    • Simple, easy to understand
    • Inheritance is captured in a natural, modular fashion
    • Frames support efficient inference by following links
  35. Five disadvantages of frame-based systems:
    • Negation cannot be represented uniformly
    • Disjunction cannot be represented naturally - Jim has either mumps or rubella
    • Quantification is not a part of the language - All of Jim’s diseases are infectious
    • No standard way to represent exceptions
    • Assumes a closed-world assumption - Everything that is true is known to be true, therefore everything that is not stated is false
  36. Name two examples of a frame-based system in biomedicine.
    • Internist-1, and it's predecessor, Quick Medical Reference (QMR)
    • FMA (Formal Model of Anatomy)
  37. What did the creators of Internist-1 and QMR record? In what form is this?
    • For each internal medicine disease, the creators recorded the evoking strength, frequency, and importance of many symptoms/physical exam findings.
    • This was in the form of Frames.
  38. Internist-1 and QMR: Each _____ had a frame and the frame stored the findings for the evoking strength, frequency, and importance of many symptoms/physical exam findings.
  39. Internist-1 and QMR: when you entered in _________, the system created a differential by ranking diseases by rewarding diseases that contained the most common and most differentiating symptoms and penalizing diseases that didn’t have those
    symptoms/findings for an actual patient
  40. Internist-1 and QMR: input
    user enters patient's findings
  41. Internist-1 and QMR: output
    differential diagnosis
  42. Internist-1 and QMR: two uses
    • Disease complications: Can explain diseases that may result from complications of the primary disease
    • Helps to “rule in” diagnosis: Suggests additional findings that would support diagnosis, Assists in ordering additional tests
  43. How to integrate frames and rules:
    • Rules act on information stored within frames
    • Left-hand side of rules refer to frames that may become instantiated at run time
    • Right-hand sides of rules conclude values that alter instantiations of frames or that instantiate new frames
  44. Integrating frames and rules example:
    Frame: Bob is an individual of the Frog concept
    Rules: IF X is a frog, THEN X is green

    What can we do now?
    We can now use the rule to update our frame for Bob to have the role (data property) that he is green
  45. First-order logic is the ____ expressive option for representing knowledge, but computation can be intractable
  46. FOL
    first order logic
  47. FOL quantifiers
    for all, there exists
  48. FOL logical connectives
    and, or, exclusive or, implies
  49. FOL predicates
    • Describe variables and relationships between variables
    • Diagnosis(X, anemia)
    • Male(Y)
    • Patient(Z)
  50. Six components of FOL
    • quantifiers
    • logical connectives
    • negation
    • predicates
    • variables
    • function
  51. OWL is what kind of knowledge representation?
    description logic
  52. for most ontologies, people use ____ to build them
  53. OWL
    Web Ontology Language
  54. Four advantages of description logic
    • Open-world assumption: Just because something hasn’t been said yet, doesn’t mean it is not true
    • Automatic classification of new concepts
    • Automatic identification of redundant concepts
    • Ease of customization when customers require specialized terms
  55. precise notation for representing noun phrases
    description logic
  56. fundamental ontology of description logics
    • conceptual model is populated by:
    • individuals
    • related by binary relationships (roles and features)
    • grouped into classes (concepts)
  57. Three uses of description logic:
    • 1. subsumption: is category C1 a subset of C2?
    • 2. classification: does object O belong to C?
    • 3. satisfiability: can category C ever be instantiated?
  58. Closed-world assumption, give an example
    • What is not known to be true must be false
    • Frame-based systems, rule-based systems, FOL
  59. open-world assumption, give an example
    • Unstated things are unknown
    • Just because someone hasn’t said it yet, doesn’t mean it isn’t true
    • Description logic uses an open-world assumption
  60. ​If we had an OWL (description logic) knowledge base that contained only a statement that said “all cats are animals”, what would we conclude about a new statement that says “all cats are soft”?
    This new statement is not entailed from the current knowledgebase, but it is not contradicted by it either. Since we’re using OWL, which is based in DL, and the open­world assumption holds in DL, then we accept the new statement into the knowledgebase as true, but can’t conclude anything more about animals.
  61. Many DLs are _________ of first-order logic (FOL).
    decidable fragments
  62. description logic: classification
    Classification takes a new Concept and automatically determines all subsumption relations between it and all other Concepts in the network
  63. true/false - description logic: Adds new links when new subsumption relations are discovered
  64. DL: automates the placement of new ______ in the taxonomy
  65. DL: The classifier takes care of where to place a new concept in the ______
  66. DL: All ________ are automatically propagated to the new concept
    inheritance relationships
  67. DL: Relationships among a new concept and other entities are automatically simplified by classifying the new concept as a ______ of existing concepts
  68. DL restrictions: Each individual of a concept will have certain _____ (aka Data Properties and Object Properties). We can put restrictions on the type of data and objects linked together with these ____
  69. DL cardinality restrictions
    minCardinality, maxCardinality: Must have at least/most X values entered
  70. DL is good for representing...
    discrete, clear descriptions of facts/relationships
  71. DL is not good for representing ...
    things like multi-valued relations and probabilistic relations (or anything other than descriptions)
  72. two examples of limitations of DL in biomedical applications
    • A patient may have some subset of symptoms but its not clear how many of the symptoms a patient needs before they reach a diagnosis. Some symptoms may be more important than others. 
    • A patient’s symptoms give clues about the probability of disease more often than they definitively denote a disease.
  73. Biomedical application that uses DL
  74. semantics and the "meaning triangle"
    • There is an object/thing in the real world (e.g. Down Syndrome)
    • We have a mental concept for what that object is
    • We have a symbol to represent that object and how we conceive it so that we can communicate the thought of the object to other people and to computers
    • For example, it could be an instance of the class Developmental Disease and have certain symptom properties
  75. model
    anything used to represent any subject matter in order to help us to understand this subject matter
  76. “Competency questions”
    • Provide a good start for building a model
    • Use to limit the scope of the model
    • Which wine characteristics should I consider when choosing a wine?
    • Is Bordeaux a red or white wine?
  77. What is MIAME?
    • Minimum Information About a Microarray Experiment
    • Describes the minimum information required to ensure that microarray data can be easily interpreted and that results derived from its analysis can be independently verified.
    • The ultimate goal of this work is to establish a standard for recording and reporting microarray-based gene expression data, which will in turn facilitate the establishment of databases and public repositories and enable the development of data analysis tools.
  78. The Problem-Oriented Medical Record
    • Elements of EHR
    • Dr. Larry Weed
    • Created new model based on patient problems
    • 1971
  79. What does SOAP stand for?
    • S: subjective data
    • O: objective data
    • A: assessment
    • P: plan
    • Every problem is numbered
    • Description of problem may change over time with new information
    • Number for each problem never gets recycled
  80. Controlled terminologies: diseases
    ICD-10, ICD-10-CM, DRG
  81. controlled terminologies: Procedures
    CPT-5, ICD-10-PCS
  82. controlled terminologies: laboratory tests
  83. controlled terminologies: nursing activities
    NIC, NOC, HHCC, Omaha
  84. controlled terminologies: drugs
    Multum, Micromedex, NDFRT
  85. controlled terminologies: biomedical literature
  86. controlled terminologies: clinical documentation
    Medcin, Purkinjie
  87. controlled terminologies: cross-references among terminologies
  88. What is SNOMED Clinical Terms (SNOMED CT)?
    A systematically organized collection of medical terms providing codes, terms, synonyms and definitions used in clinical documentation and reporting.
  89. SNOMED-CT uses ____ to relate terms
    description logic
  90. ______ system contains codes for diseases, signs and symptoms, abnormal findings, complaints, social circumstances, and external causes of injury or diseases
    ICD code
  91. ICD codes are used for (5 uses)
    • Disease surveillance and public health
    • Institutional planning
    • Quality assurance
    • Economic modeling
    • Billing and reimbursement
  92. Current Procedural Terminology (CPT)
    • Provides a code for every type of medical procedure
    • Relationships between codes are implicit
    • Example: Code 93571 codes for an intravascular doppler measurement during a coronary angiogram. Then Code 93572 is the code for each additional vessel that you measure after measuring the first one. The definition of Code 93572 does not make any explicit mention of Code’s just implied.
  93. Logical Observations, Identifiers, Names and Codes (LOINC)
    • Standardized terminology for lab tests
    • Codes enumerate highly structured attributes of laboratory observations (e.g., substance measured, analytical method used)
    • No hierarchical organization
  94. Unified Medical Language System (UMLS)
    provides a way to unify all of the other ontologies (diseases, procedures, lab tests, etc)
  95. UML uses _____ semantics to define relative equivalence of concepts and relationships among concepts
  96. UML provides a metathesaurus of more than 40 “source terminologies,” with more than 331,000 terms. Provides a ____ for each entry
    Concept Unique Identifier (CUI)
  97. Health Level-7
    Health Level-7 or HL7 refers to a set of international standards for transfer of clinical and administrative data between software applications used within a give hospital...lets a health system share data across its domains
  98. Problems with HL7 V3 (4 problems)
    • The models and messages were too complex - Average HL7 V3 message had 5–10 times the number of XML nodes as messages in other industries
    • The RIM tried to model everything, with maximum extensibility and generality
    • The standard lacked a useful mechanism to add extensions
    • Documentation was poor
  99. Fast Healthcare Interoperability Resources (FHIR) was based on
    Version 3 RIM
  100. FHIR Adopts ____ rule to simplify things.
    • "80/20"
    • make life simpler for implementers, rather than for modelers
  101. FIHR used a ____ approach
    • modular
    • "Resources"
    • Small contained model
    • Concepts related to a particular thing
    • e.g. medication prescription, adverse reaction
    • Discrete, but may reference one another, forming a graph
  102. FHIR was made to be easily extended by developers at deployment sites. FHIR ____  determine terminologies, restrictions, etc
  103. HL7 V2, RIM, and FHIR were designed to provide interoperability _____ institutions by modeling individual, clinically relevant concepts.
  104. CDA helps you package up data from one health system so ...
    it can be shared with another health system
  105. Health Information Exchange (HIE) goals (3 things)
    • How to package up composite information for transfer *across* institutions?
    • Mobilization of patient data electronically across regions, communities, or health-care organizations
    • Enables exchange of information across disparate information systems
    • Goals are
    • To enable more coordinated, timely, efficient care
    • To aid public health reporting and clinical research
  106. CDA (Clinical Document Architecture) is a model for
    a clinical document
  107. CDA (Clinical Document Architecture) based on
  108. CDA (Clinical Document Architecture) facilitates exchange of clinical documents ______ health care organizations.
    within and between
  109. CDA (Clinical Document Architecture) is a _______ for marking up narrative clinical reports—putting a wrapper around packages of clinical data
    XML-based language,
  110. CDA (Clinical Document Architecture) allows document text to be marked up with terms from the...
    RIM and from controlled terminologies
  111. Continuity of Care Document (CCD) - A joint effort of ...
    HL7 International and ASTM.
  112. CCD fosters interoperability of clinical data by ...
    allowing physicians to send electronic medical information to other providers without loss of meaning and enabling improvement of patient care.
  113. CCD
    Continuity of Care Document
  114. CCD is an implementation guide for sharing Continuity of Care Record (CCR) patient summary data using the ...
    HL7 Version 3 Clinical Document Architecture (CDA)
  115. ontologies
    • formal specification of a shared conceptualization
    • Conceptualization: the way we think about a domain
    • Specification: formal way of writing it down
  116. Levels of ontological depth (5 levels)
    • lexicon
    • simple taxonomy
    • thesaurus
    • relational model
    • fully axiomatized theory
  117. lexicon
    vocabulary, possibly with natural-language definitions
  118. simple taxonomy
    terms with class-subclass relations
  119. thesaurus
    taxonomy plus related terms
  120. relational model
    unconstrained use of arbitrary relations
  121. Basic Formal Ontology provides an ____ that you can use to combine several lower-level ontologies
    upper-level ontology
  122. Use cases for ontologies (3)
    • Share common understanding of the entities in a given domain - Among people, software agents, between people and software
    • Enable reuse of data and information - Introduce standards to allow interoperability and automatic reasoning - Create communities of researchers
  123. Sketch out how you will model the classes for an ontology that will be used to classify and understand the variation in doctor’s notes amongst chronically ill and acutely ill patients.
    What are the classes?
    • patients - chronically ill, acutely ill
    • care providers - doctors, nurses
    • notes - histories, updates
  124. Sketch out how you will model the classes for an ontology that will be used to classify and understand the variation in doctor’s notes amongst chronically ill and acutely ill patients.
    What are relationships between classes?
    • care providers write notes
    • doctors have patients
    • notes pertain to patients
  125. upper-level ontologies
    Ontology that consists of very general terms (such as “object”, “property”, “relation”) that are common across all domains
  126. upper-level ontologies function (3)
    • Support broad semantic interoperability among a large number of domain-specific ontologies
    • Provides a common starting point for the formulation of definitions
    • Domain ontology terms are ranked under terms of upper ontology - I.e. upper ontology classes are superclasses or supersets of all classes in domain ontologies
  127. upper-level ontologies advantages (3)
    • Upper-level classes provide a useful organizing structure
    • Upper-level classes minimize the chance of category errors
    • Standard upper-level ontologies aid alignment and reuse across ontologies
  128. Basic Formal Ontology (BFO)
    • Small, upper level ontology
    • Designed for supporting information retrieval, analysis and integration in scientific and other domains
    • Does not contain physical, chemical, biological or other terms that fall within domain ontologies
  129. ontology engineering: clarity
    definitions should be objective and complete
  130. ontology engineering: coherence
    • Ontology should sanction those inferences consistent with the definitions
    • No concepts exist that are unsatisfiable (interpreted as a empty set)
  131. ontology engineering: extendibility
    Should anticipate future uses
  132. ontology engineering: minimal encoding bias
    No assumptions about knowledge representation
  133. ontology engineering: minimal ontological commitment
    Say no more than is necessary
  134. 6 steps in building an ontology
    • Determine the scope that your ontology needs to cover - Consider how it will be used and how it might need to be used in the future when deciding how detailed you want it to be. 
    • Enumerate the terms that need to be covered by the ontology
    • Define your classes (concepts)
    • Define the roles (aka data properties and object properties) of each class
    • Define constraints for these properties
    • Create instances
  135. Important ontologies used in biomedicine (4)
    • Gene Ontology (GO)
    • Foundational Model of Anatomy (FMA)
    • MYCIN
  136. Gene Ontology (GO): three ontologies
    • 1. molecular function - elemental activity or task, DNA binding
    • 2. cellular component - location or complex, cell nucleus
    • 3. biological process - goal or objective within cell, secretion
  137. GO uses (3)
    • Suggesting biological process associated with expressed genes
    • Enables analysis of how genes cluster together based on functional properties
    • Using gene annotations to custom-design microarrays based on biological processes of interest
  138. Foundational Model of Anatomy (FMA)
    • Knowledgebase of anatomy information
    • Well-developed
  139. Foundational Model of Anatomy (FMA) ____ declares principles necessary for modeling the concepts and relationships
  140. Foundational Model of Anatomy (FMA) Originally created as a ...
    frame hierarchy - Concepts, attributes, relations
  141. Foundational Model of Anatomy (FMA) uses a well formed, domain-specific ...
    upper-level ontology - Anatomical spatial entity, anatomical structure, body substance
  142. MYCIN used a ____ for its ontology and ____ (2) for its Problem Solving Methods
    • rule-based system
    • certainty factors and backward chaining
  143. When MYCIN asked the user a question to supply the value of a parameter, MYCIN would print out ...
    a translation of a rule that has the parameter in its premise
  144. INTERNIST-1/QMR used a _____ for its ontology and used ____ for its problem solving method
    • frame-based system
    • its own brand of ad-hoc system (ranking algorithm, heuristic rules)
  145. INTERNIST-1/QMR mimicked
    hypothetico-deductive reasoning as performed by human experts (considered the importance and frequency of each symptom in relation to each disease to rank diseases in a differential diagnosis)
  146. QMR-DT (Quick Medical Reference-Decision Theory) replaced the ad-hoc method of INTERNIST-1 with
    • a Bayesian Belief Network
    • They mapped the frequency rankings (1 to 5) in the ad-hoc system to conditional probabilities so that they could get P(symptom | disease)
  147. Languages used for specifying ontologies (4)
    • UML
    • Common Logic
    • Web languages - XML, OWL
  148. Common problems building ontologies (3)
    • Entities are not defined at useful levels of abstraction - Necessary to distinguish between mammals and dogs?
    • Entity definitions are overloaded - Helpful to have the class red bicycle?
    • Hierarchical relationships are not uniformly taxonomic - Amino acid is a descendant of protein
  149. Minimizing ontological commitment requires specifying ...
    a weak theory
  150. Making definitions precise requires increasing ...
    ontological commitment
  151. Anticipating various uses of the ontology may require increasing the number of ...
    concepts represented
  152. Making an ontology maximally general may make it useless for ...
    any specific application
  153. Domains of systems
    The subject area of a system (e.g. infectious diseases)
  154. Tasks
    Activities within a domain that a system performs (e.g. diagnosis)
  155. Problem solving Methods (PSMs)
    The procedures used to carry out the tasks (e.g. classification)
  156. Process for task modeling (4 steps):
    • Characterize the overall task
    • Identify a method that solves that task, entailing any number of subtasks
    • For each subtask, identify a method that solves that subtask
    • Terminate when there is a well-described method for solving each subtask
  157. Heuristic Classification PSM
    Heuristic classification is suitable for classification problems in which it is known from experience which observations— or combinations of observations — indicate intermediate or final solutions, and with what degree of certainty.
  158. Hierarchical task analysis
    • In order to accomplish a big, complex task, you need to break it down into sub-tasks that can be solved with the PSMs that you have. 
    • 1. Identify the task you want to accomplish
    • 2. Create a PSM that can solve it
    • 3. Identify the sub-tasks that must be solved to accomplish the PSM
    • 4. Create the PSMs necessary to accomplish the sub-task...
    • The result is a structure that defines how problem solvers should be invoked
  159. To rule in a diagnosis (specificity/sensitivity)?
    • To help conclude a diagnosis of which you are suspicious
    • SpPIn
    • Specific test when Positive, rules In
  160. To rule out a diagnosis (specificity/sensitivity)?
    • To help to determine that an unlikely diagnosis is not present
    • SnNOut
    • Sensitive test when Negative Rules Out
  161. Ad hoc methods: resulted from
    Resulted from a mistrust of Bayesian statistics
  162. Ad hoc methods: name two
    (Certainty factors, fuzzy logic)
  163. MYCIN “certainty factor” model
    • Adopts a measure of belief that ranged from -1.0 (complete falsehood) to +1.0 (complete truth)
    • Requires each rule to include a certainty factor for its conclusion
    • Requires the runtime system to update the CF for a proposition dynamically as each rule fires
    • Requires threshold for acceptance or rejection of a proposition
  164. MYCIN “certainty factor” model problems
    • Does not overcome the conditional independence assumption - Highly related findings (e.g. fever, chills, and sweats) all individually increase posterior probability of disease (eg influenza)
    • Assessing “correct” CFs is difficult - There is no direct translation from statistical data to CFs
    • Developers assigning CFs have a tendency to conflate probabilistic values with other considerations - I.e. more important conclusions may be assigned higher CFs
  165. Fuzzy set theory and fuzzy logic
    • Truth is not binary but a continuous value between 0 and 1
    • Reflecting the degree of membership in a fuzzy set
    • Goal is to infer degree of truth
    • Unlike probability theory, where goal is to determine likelihood of situations
    • Process of fuzzification
    • Converts numerical values into confident levels for membership in a fuzzy set
  166. Assumptions often used when applying Bayes theorem (3)
    • Disease in the differential diagnosis are assumed to be mutually exclusive
    • Differential diagnosis is assumed to include the correct diagnosis (complete)
    • Observations supporting the diagnosis are assumed to be conditionally independent when seen in the setting of any of the diseases in the differential diagnosis
  167. Belief Networks (Bayes Nets) provide a way to represent ______ between random variables. Nodes store probabilities _______ on only those nodes to which they are connected, reduces required computation!
    • conditional dependencies
    • conditioned
  168. To “solve” the Bayes belief network: (3)
    • Users enter the state of those nodes for which the state is known (e.g., person went to Honey-Baked Ham)
    • Algorithm calculates the posterior probability of all possible states of the remaining nodes (e.g., patient has swine flu)
    • If no state values are entered, then the initial probability of each value of each node is simply the prior probability
  169. First-order logic vs Markov Logic
    • Markov Logic (the kind of logic used in Bayesian reasoning) is probabilistic. Therefore, you can have two opposing statements that each have some probability of being true
    • In a traditional FOL knowledgebase, every statement must be true (with probability one, so to speak), so having two opposing statements would make the knowledgebase incoherent.
  170. Options for how to evaluate diagnostic systems (5)
    • Producing the correct diagnosis? -At the top of the list of candidates? - Somewhere within the list of candidates?
    • The “quality” of the differential diagnosis?User acceptance/satisfaction?
    • Amount of use of the system?
    • Appropriate management suggestions?
  171. Questions about an artifact (7)
    • Is there a need for it?
    • Does it work?
    • How fast does it work?
    • Does it work reliably?
    • Do people use it?
    • Which parts cause which effects?
    • How can it be improved?
  172. Questions about the impact of an artifact (7)
    • Do people like it?
    • Does it improve efficiency of performing some task?
    • Does it improve accuracy of performing some task?
    • Does it influence the collection of data?
    • Does it influence users’ decisions
    • Does it affect third parties (e.g., patients)
    • How long do the observed effects last?
  173. Formative versus Summative evaluation
    • Formative: How can be build better systems?
    • Summative: What can we conclude about a system that has been built?
  174. Objectivist
    • What can we measure and compare about a system?
    • Quantitative or hard research
  175. Objectivist Evaluation approach
    • Logical-positivist perspective
    • Assumes that questions can be answered in terms of attributes and can be measured
    • Assumes that rational people can and should agree a priori what attributes are important to measure
    • Assumes that precise numbers are better than imprecise verbal descriptions
  176. Objectivist approach advantages
    Can be relatively easy to do
  177. Objectivist approach disadvantages
    May not measure the most important results
  178. MYCIN evaluation used _____ standard to judge therapy. It showed how ___ it was to reach a consensus on appropriate theory.
    • peer review
    • difficult
    • Anonymous computer or human recommendation
    • Limitations
    • Relatively few cases and evaluators but still arduous to conduct
    • Says nothing about usability
    • Claims that expert-level performance was meaningless
    • System could not fit into real clinical workflow, despite excelling expert-level performance
  179. Subjectivist
    • What can we infer from observation of a system
    • Qualitative or pejoratively, soft research
  180. Subjectivist approach assumes what is observed about a resource depends on ...
    the observer
  181. The subjectivist approach assumes the value of a resource depends on its _____, and saliency of attributes is _____dependent
Card Set
BMI 210: Modeling Biomedical Systems
Modeling Biomedical Systems