Cognitive map to support the diagnosis of solitary bone tumors in pediatric patients

Abstract

ObjectiveTo present a cognitive map to support the radiological diagnosis of solitary bone tumors, as well as to facilitate the determination of the nature of the tumor (benign or malignant), in pediatric patients.Materials and MethodsWe selected 28 primary lesions in pediatric patients, and we identified the findings typically associated with each of the diagnoses. The method used for the construction of the final cognitive map was the Bayesian belief network model with backward chaining.ResultsWe developed a logical, sequential structure, in the form of a cognitive map, based on the Bayesian belief network model, with the intention of simulating the sequence of human thinking, in order to minimize the number of unnecessary interventions and iatrogenic complications arising from the incorrect evaluation of bone lesions.ConclusionWith this map, it will be possible to develop an application that will provide support to physicians and residents, as well as contributing to training in this area and consequently to a reduction in diagnostic errors in patients with bone lesions.

Radiological aspects in computed tomography as determinants in the diagnosis of pulmonary tuberculosis in immunocompetent infants

“…Imaging tests have recently been the focus of studies in the radiology literature (29)(30)(31)(32)(33)(34)(35) . Although there have been several studies on the radiological imaging of childhood tuberculosis, our study is comparable only to those that have used CT and have involved patients in the same age group.…”

"Don't touch" bone lesions: how can we contribute?

“…There is currently a tendency to use computerized systems to support the clinical decision and diagnosis, contributing to the management of medical knowledge. In a recent article addressing this theme, Moreira et al ( 7 ) described a cognitive mapping system specifically focused on supporting the diagnosis of solitary bone tumors in pediatric patients, with the objective of supporting the decisions of medical professionals and promoting training in the area, potentially reducing errors in the diagnosis of such lesions. Costa ( 8 ) also recently discussed the application of artificial intelligence in the evaluation of bone tumors, highlighting the great potential of such tools.…”

Evaluation of musculoskeletal tumors in the new era of artificial intelligence

“…The development of a cognitive map for the detection of solitary bone tumors in childhood would become an essential part of clinical practice, as a complement to diagnostic imaging, allowing the correct strategic interpretation of the diagnoses made, with little error variance. It would be possible to create an application to support professionals in the area, globally, reducing iatrogenic errors and minimizing the number of inaccurate diagnoses, as well as the negative consequences thereof ( 5 ) .…”