TY  - JOUR
AU  - Sustersić, Tijana
AU  - Ranković, Vesna
AU  - Peulić, Miodrag
AU  - Peulić, Aleksandar
PY  - 2020
UR  - https://gery.gef.bg.ac.rs/handle/123456789/1055
AB  - 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 specificity. Very weak or no correlation was observed between gender and disc hernia diagnosis (or obesity type and disc hernia diagnosis). Obtained results show that this method can be used in initial screening of patients and be a supportive tool to doctors to send the same patients for further examination.
PB  - IEEE -Inst Electrical Electronics Engineers Inc, Piscataway
T2  - IEEE Journal of Biomedical and Health Informatics
T1  - An Early Disc Herniation Identification System for Advancement in the Standard Medical Screening Procedure Based on Bayes Theorem
VL  - 24
IS  - 1
SP  - 151
EP  - 159
DO  - 10.1109/JBHI.2019.2899665
UR  - https://hdl.handle.net/21.15107/rcub_gery_1055
ER  - 

@article{
author = "Sustersić, Tijana and Ranković, Vesna and Peulić, Miodrag and Peulić, Aleksandar",
year = "2020",
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 specificity. Very weak or no correlation was observed between gender and disc hernia diagnosis (or obesity type and disc hernia diagnosis). Obtained results show that this method can be used in initial screening of patients and be a supportive tool to doctors to send the same patients for further examination.",
publisher = "IEEE -Inst Electrical Electronics Engineers Inc, Piscataway",
journal = "IEEE Journal of Biomedical and Health Informatics",
title = "An Early Disc Herniation Identification System for Advancement in the Standard Medical Screening Procedure Based on Bayes Theorem",
volume = "24",
number = "1",
pages = "151-159",
doi = "10.1109/JBHI.2019.2899665",
url = "https://hdl.handle.net/21.15107/rcub_gery_1055"
}

Sustersić, T., Ranković, V., Peulić, M.,& Peulić, A.. (2020). An Early Disc Herniation Identification System for Advancement in the Standard Medical Screening Procedure Based on Bayes Theorem. in IEEE Journal of Biomedical and Health Informatics
IEEE -Inst Electrical Electronics Engineers Inc, Piscataway., 24(1), 151-159.
https://doi.org/10.1109/JBHI.2019.2899665
https://hdl.handle.net/21.15107/rcub_gery_1055

Sustersić T, Ranković V, Peulić M, Peulić A. An Early Disc Herniation Identification System for Advancement in the Standard Medical Screening Procedure Based on Bayes Theorem. in IEEE Journal of Biomedical and Health Informatics. 2020;24(1):151-159.
doi:10.1109/JBHI.2019.2899665
https://hdl.handle.net/21.15107/rcub_gery_1055 .

Sustersić, Tijana, Ranković, Vesna, Peulić, Miodrag, Peulić, Aleksandar, "An Early Disc Herniation Identification System for Advancement in the Standard Medical Screening Procedure Based on Bayes Theorem" in IEEE Journal of Biomedical and Health Informatics, 24, no. 1 (2020):151-159,
https://doi.org/10.1109/JBHI.2019.2899665 .,
https://hdl.handle.net/21.15107/rcub_gery_1055 .