The art of building decision trees

Design of an algorithm for the diagnostic approach of patients with joint pain

BACKGROUND

Rheumatic diseases are a reason for frequent consultation with primary care doctors. Unfortunately, there is a high percentage of misdiagnosis.

OBJECTIVE

To design an algorithm to be used by primary care physicians to improve the diagnostic approach of the patient with joint pain, and thus improve the diagnostic capacity in four rheumatic diseases.

METHODS

Based on the information obtained from a literature review, we identified the main symptoms, signs, and paraclinical tests related to the diagnosis of rheumatoid arthritis, spondyloarthritis with peripheral involvement, systemic lupus erythematosus with joint involvement, and osteoarthritis. We conducted 3 consultations with a group of expert rheumatologists, using the Delphi technique, to design a diagnostic algorithm that has as a starting point "joint pain" as a common symptom for the four diseases.

RESULTS

Thirty-nine rheumatologists from 18 countries of Ibero-America participated in the Delphi exercise. In the first consultation, we presented 94 items to the experts (35 symptoms, 31 signs, and 28 paraclinical tests) candidates to be part of the algorithm; 74 items (25 symptoms, 27 signs, and 22 paraclinical tests) were chosen. In the second consultation, the decision nodes of the algorithm were chosen, and in the third, its final structure was defined. The Delphi exercise lasted 8 months; 100% of the experts participated in the three consultations.

CONCLUSION

We present an algorithm designed through an international consensus of experts, in which Delphi methodology was used, to support primary care physicians in the clinical approach to patients with joint pain. Key Points • We developed an algorithm with the participation of rheumatologists from 18 countries of Ibero-America, which gives a global vision of the clinical context of the patient with joint pain. • We integrated four rheumatic diseases into one tool with one common symptom: joint pain. It is a novel tool, as it is the first algorithm that will support the primary care physician in the consideration of four different rheumatic diseases. • It will improve the correct diagnosis and reduce the number of paraclinical tests requested by primary care physicians, in the management of patients with joint pain. This point was verified in a recently published study in the journal Rheumatology International (reference number 31).

A combined Fuzzy Cognitive Map and decision trees model for medical decision making

Fuzzy Cognitive Maps (FCMs) are an efficient modeling method providing flexibility on the simulated system's design. They consist of nodes-concepts and weighted edges that connect the nodes and represent the cause and effect relationships among them. The performance of FCMs is dependent on the initial weight setting and architecture. This shortcoming can be alleviated and the FCM model can be enhanced if a fuzzy rule base (IF-THEN rules) is available. This research proposes a successful attempt to combine fuzzy cognitive maps with decision tree generators. A combined Decision Tree-Fuzzy Cognitive Map (DT-FCM) model is proposed when different types of input data are available and the behavior of this model is studied. In this research work, we introduce a new hybrid modeling methodology for decision making tasks and we implement the proposed methodology at a medical problem.