Fuzzy logic and causal reasoning with an 'n' of 1 for diagnosis and treatment of the stroke patient

Expert Review of Neurotherapeutics

Volumn 4, Issue 2, 2004, Pages 249-254

  Helgason, Cathy M ^a   Jobe, Thomas H ^b  

^a UNIVERSITY OF ILLINOIS   (United States)

^b UNIVERSITY OF ILLINOIS AT CHICAGO   (United States)

Author keywords

Diagnosis; Fuzzy logic; Numeracy; Perceptions; Stroke; Treatment

Indexed keywords

CLINICAL PRACTICE; DISEASE CLASSIFICATION; EXPERT SYSTEM; HUMAN; REVIEW; STROKE; THEORETICAL MODEL; TREATMENT PLANNING;

CEREBROVASCULAR ACCIDENT; EVIDENCE-BASED MEDICINE; FUZZY LOGIC; HUMANS; MODELS, BIOLOGICAL;

EID: 1542314349     PISSN: 14737175     EISSN: None     Source Type: Journal    
DOI: 10.1586/14737175.4.2.249     Document Type: Review

References (12)

1. Helgason CM, Malik DS, Cheng S-C, Jobe TH, Mordeson JN. Statistical versus fuzzy measures of interaction in patients with stroke. Neuroepidemiology 20, 77-84 (2001). Shows how separation of the elements from the patient can led to detection of interactions not present in nature.
2. Helgason CM, Jobe TH. The fuzzy hypercube and causal efficacy. Representation of concomitant mechanisms in stroke. Neural Networks 11, 549-555 (2998). Original paper addressing diagnosis of stroke subtype using fuzzy logic and the unit hypercube.
3. Helgason CM, Jobe TH. Perception-based reasoning and fuzzy cardinality provide direct measures of causality sensitive to initial conditions in the individual patient. Int. J. Computational Cog. 1, 79-104 (2003). Original paper deriving fuzzy causality measures.
4. Zadeh L. From computing with numbers to computing with words-from manipulation of measurements to manipulation of perceptions. IEEE Transaction Circuits Sys. 45, 105-109 (1999). Discoverer of fuzzy sets.
5. Sacket DL, Richardson WS, Rosenberg W, Haynes RB. Evidence-Based Medicine. Churchill Livingston, Edinburgh, UK (1998).
6. Helgason CM, Jobe TH. Measurable differences between sequential and parallel diagnostic decision processes for determining stroke subtype: a representation of interacting pathologies. Thromb. Haemost. 88, 210-212 (2002).
7. Zadeh L. Fuzzy Sets. Info. Con. 8, 338-353 (1995). Seminal paper on fuzzy sets, of great interest
8. Kosko B. Neural networks and fuzzy systems. A dynamical approach to machine Intelligence. Prentice Hall, NJ, USA, 274-275 (1992). Subsethood theorem of fuzzy logic explained.
9. Kosko B. Fuzziness vs. probability. Int. J. Gen. Sys. 17, 216 (1990). Seminal paper on this topic.
10. Albers G, Amarenco P, Easton DJ, Sacco RL, Teal P. Antithrombotic and thrombolytic therapy for ischemic stroke. Sixth ACCP Consensus Conference on Anti-thrombotic Therapy. Chest 119(Suppl), S308 (2001).
11. Klaff AA. Arithmetic Refresher. Dover Publications Inc., NY, USA, 218, 227 (1964).
12. Helgason CM. The application of fuzzy logic to the prescription of antithrombotic agents in the elderly. Drugs Aging (2004) (In Press). Shows how the individual patient cannot be defined by the group to which they belong relevant to causation.