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Integral Theory Diagnostic System artificial intelligence “Wayfinding” software helps unravel the complexity of multiple symptom causation prior to ligament surgery
Peter PETROS11University of Western Australia School of Mechanical and Mathematical Engineering, Perth WA, Australia
Background: A principal reason for developing diagnostic software is to reduce diagnostic error and facilitate a more accurate diagnosis. The National Academies of Sciences, Engineering, and Medicine publication “Improving Diagnosis in Health Care”, has three main themes: reduce diagnostic errors, patient involvement and how to address “the increasing complexity of health care”. Aim: To describe in principle a computerized decision-tree software Integral Theory Diagnostic System (ITDS). Materials and Methods: A node system of individual symptoms guided placement into three zones of ligament damage, anterior, middle, posterior. Percentage probabilities guided diagnosis. The system was tested against a Bayesian Network method Results: The ITDS works well as a diagnostic aid. The diagnosis of zone of damage is displayed pictorially, with deepening colours of red indicating probability of damage. A separate button describes the iteration to the diagnosis. The Bayesian method was tested only in a fairly small number of women, it was found to be equivalent or even superior to that made by the expert. Conclusion: The Integral Theory is holistic and its control non-linear. The contribution of the six main ligaments to pathogenesis and particular symptom causation may vary from patient to patient. A more developed version of the ITDS would be very helpful in assisting a more accurate diagnosis and reducing diagnostic error.
Cite This Article
PETROS P. Integral Theory Diagnostic System artificial intelligence “Wayfinding” software helps unravel the complexity of multiple symptom causation prior to ligament surgery. 2022; 41(1): 9-12
Corresponding Author: PETROS P.
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