An Early Disc Herniation Identification System for Advancement in the Standard Medical Screening Procedure Based on Bayes Theorem

IEEE Journal of Biomedical and Health Informatics
Tijana SustersicAleksandar Peulic

Abstract

The aim of this research was to analyze objectively the process of disc herniation identification using Bayes Theorem. One of the symptoms of discus hernia is muscle weakness on the foot that is caused by displaced discs in the space of two vertebrae. This fact is used by experts in initial diagnosis of herniated discs and we used it to create non-invasive platform for the same purposes by measuring force values from four sensors placed on both feet (first, second, and fourth metatarsal head as well as the heel). Dataset consisted of several minute force recordings of 56 subjects with discus hernia and 15 healthy individuals during normal standing, standing on forefeet and heels. The subjects were diagnosed by a specialist with either L4/L5 or L5/S1 discus hernia. Collected recordings were processed in several steps including filtering, extraction of forefeet and heel recordings, classification of average values for forefeet, and heel sensors to the groups with or without foot muscle weakness. Application of Bayes Theorem on the attributes of interest showed average 78.3% accuracy with 62.6% sensitivity and 80.9% specificity, while application of naive Bayes Network showed average 83.1% accuracy with 57.6% sensitivity and 88.2%...Continue Reading

Citations

Aug 30, 2020·Computers in Biology and Medicine·Tijana ŠušteršičNenad Filipović
Mar 5, 2021·Network and Systems Medicine·Massimiliano ZaninHarald H H W Schmidt

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