Wound Classifications Of Breast Tissues with Electrical Impedance Spectroscopy (EIS): Comparison of LVQ and GA-LVQ

Yoke Kusuma Arbawa; R. Adhitya Dwi Pisefty; Fitra A. Bachtiar

doi:10.1109/ICSITech46713.2019.8987447

Wound Classifications Of Breast Tissues with Electrical Impedance Spectroscopy (EIS): Comparison of LVQ and GA-LVQ

Yoke Kusuma Arbawa
, R. Adhitya Dwi Pisefty
, Fitra A. Bachtiar

Faculty of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

Deaths of people with breast diseases have reached 40% and are increasing every year. Breast Disease arises from wounds in breast tissue is breast cancer. Wounds of breast can be seen and discriminated the type of wound using Electrical Impedance Spectroscopy(EIS). The results of this EIS data can be used as an initial diagnosis before the doctor carries out treatment. This research tried to classify the types of wounds from breast tissue by using the Learning Vector Quantization (LVQ) method with the Genetic Algorithm (GA) to find out whether the solution provides the expected optimum results. The dataset we used for this study was very small which did not represent the existing class, with 106 data for 6 classes. The results of the comparison between LVQ and GA-LVQ obtained LVQ added by GA has higher accuracy values than LVQ with 73% accuracy and compared to LVQ, GA increased accuracy by ± 50%.

Original language	English
Title of host publication	Proceeding - 2019 5th International Conference on Science in Information Technology
Subtitle of host publication	Embracing Industry 4.0: Towards Innovation in Cyber Physical System, ICSITech 2019
Editors	Awang Hendrianto Pratomo, Andri Pranolo, Leonel Hernandez, Rafal Drezewski, Roman Voliansky, Mohamad Shanudin Zakaria, Bagus Muhammad Akbar, Shoffan Saifullah, Ahmad Taufiq Akbar, Rochmat Husaini, Heriyanto Heriyanto, Andiko Putro Suryotomo, Vynska Amalia Permadi, Sylvert Prian Tahalea
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	229-234
Number of pages	6
ISBN (Electronic)	9781728123806
DOIs	https://doi.org/10.1109/ICSITech46713.2019.8987447
Publication status	Published - Oct 2019
Event	5th International Conference on Science in Information Technology, ICSITech 2019 - Yogyakarta, Indonesia Duration: 23 Oct 2019 → 24 Oct 2019

Publication series

Name	Proceeding - 2019 5th International Conference on Science in Information Technology: Embracing Industry 4.0: Towards Innovation in Cyber Physical System, ICSITech 2019

Conference

Conference	5th International Conference on Science in Information Technology, ICSITech 2019
Country/Territory	Indonesia
City	Yogyakarta
Period	23/10/19 → 24/10/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Breast tissue
Classification
Genetic Algorithm-Learning Vector Quantization
Learning Vector Quantization

Access to Document

10.1109/ICSITech46713.2019.8987447

Cite this

Arbawa, Y. K., Pisefty, R. A. D., & Bachtiar, F. A. (2019). Wound Classifications Of Breast Tissues with Electrical Impedance Spectroscopy (EIS): Comparison of LVQ and GA-LVQ. In A. H. Pratomo, A. Pranolo, L. Hernandez, R. Drezewski, R. Voliansky, M. S. Zakaria, B. M. Akbar, S. Saifullah, A. T. Akbar, R. Husaini, H. Heriyanto, A. P. Suryotomo, V. A. Permadi, & S. P. Tahalea (Eds.), Proceeding - 2019 5th International Conference on Science in Information Technology: Embracing Industry 4.0: Towards Innovation in Cyber Physical System, ICSITech 2019 (pp. 229-234). Article 8987447 (Proceeding - 2019 5th International Conference on Science in Information Technology: Embracing Industry 4.0: Towards Innovation in Cyber Physical System, ICSITech 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSITech46713.2019.8987447

Arbawa, Yoke Kusuma ; Pisefty, R. Adhitya Dwi ; Bachtiar, Fitra A. / Wound Classifications Of Breast Tissues with Electrical Impedance Spectroscopy (EIS) : Comparison of LVQ and GA-LVQ. Proceeding - 2019 5th International Conference on Science in Information Technology: Embracing Industry 4.0: Towards Innovation in Cyber Physical System, ICSITech 2019. editor / Awang Hendrianto Pratomo ; Andri Pranolo ; Leonel Hernandez ; Rafal Drezewski ; Roman Voliansky ; Mohamad Shanudin Zakaria ; Bagus Muhammad Akbar ; Shoffan Saifullah ; Ahmad Taufiq Akbar ; Rochmat Husaini ; Heriyanto Heriyanto ; Andiko Putro Suryotomo ; Vynska Amalia Permadi ; Sylvert Prian Tahalea. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 229-234 (Proceeding - 2019 5th International Conference on Science in Information Technology: Embracing Industry 4.0: Towards Innovation in Cyber Physical System, ICSITech 2019).

@inproceedings{261d6e58f8734863880d0a66a12442c0,

title = "Wound Classifications Of Breast Tissues with Electrical Impedance Spectroscopy (EIS): Comparison of LVQ and GA-LVQ",

abstract = "Deaths of people with breast diseases have reached 40\% and are increasing every year. Breast Disease arises from wounds in breast tissue is breast cancer. Wounds of breast can be seen and discriminated the type of wound using Electrical Impedance Spectroscopy(EIS). The results of this EIS data can be used as an initial diagnosis before the doctor carries out treatment. This research tried to classify the types of wounds from breast tissue by using the Learning Vector Quantization (LVQ) method with the Genetic Algorithm (GA) to find out whether the solution provides the expected optimum results. The dataset we used for this study was very small which did not represent the existing class, with 106 data for 6 classes. The results of the comparison between LVQ and GA-LVQ obtained LVQ added by GA has higher accuracy values than LVQ with 73\% accuracy and compared to LVQ, GA increased accuracy by ± 50\%.",

keywords = "Breast tissue, Classification, Genetic Algorithm-Learning Vector Quantization, Learning Vector Quantization",

author = "Arbawa, \{Yoke Kusuma\} and Pisefty, \{R. Adhitya Dwi\} and Bachtiar, \{Fitra A.\}",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 5th International Conference on Science in Information Technology, ICSITech 2019 ; Conference date: 23-10-2019 Through 24-10-2019",

year = "2019",

month = oct,

doi = "10.1109/ICSITech46713.2019.8987447",

language = "English",

series = "Proceeding - 2019 5th International Conference on Science in Information Technology: Embracing Industry 4.0: Towards Innovation in Cyber Physical System, ICSITech 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "229--234",

editor = "Pratomo, \{Awang Hendrianto\} and Andri Pranolo and Leonel Hernandez and Rafal Drezewski and Roman Voliansky and Zakaria, \{Mohamad Shanudin\} and Akbar, \{Bagus Muhammad\} and Shoffan Saifullah and Akbar, \{Ahmad Taufiq\} and Rochmat Husaini and Heriyanto Heriyanto and Suryotomo, \{Andiko Putro\} and Permadi, \{Vynska Amalia\} and Tahalea, \{Sylvert Prian\}",

booktitle = "Proceeding - 2019 5th International Conference on Science in Information Technology",

}

Arbawa, YK, Pisefty, RAD & Bachtiar, FA 2019, Wound Classifications Of Breast Tissues with Electrical Impedance Spectroscopy (EIS): Comparison of LVQ and GA-LVQ. in AH Pratomo, A Pranolo, L Hernandez, R Drezewski, R Voliansky, MS Zakaria, BM Akbar, S Saifullah, AT Akbar, R Husaini, H Heriyanto, AP Suryotomo, VA Permadi & SP Tahalea (eds), Proceeding - 2019 5th International Conference on Science in Information Technology: Embracing Industry 4.0: Towards Innovation in Cyber Physical System, ICSITech 2019., 8987447, Proceeding - 2019 5th International Conference on Science in Information Technology: Embracing Industry 4.0: Towards Innovation in Cyber Physical System, ICSITech 2019, Institute of Electrical and Electronics Engineers Inc., pp. 229-234, 5th International Conference on Science in Information Technology, ICSITech 2019, Yogyakarta, Indonesia, 23/10/19. https://doi.org/10.1109/ICSITech46713.2019.8987447

Wound Classifications Of Breast Tissues with Electrical Impedance Spectroscopy (EIS): Comparison of LVQ and GA-LVQ. / Arbawa, Yoke Kusuma; Pisefty, R. Adhitya Dwi; Bachtiar, Fitra A.
Proceeding - 2019 5th International Conference on Science in Information Technology: Embracing Industry 4.0: Towards Innovation in Cyber Physical System, ICSITech 2019. ed. / Awang Hendrianto Pratomo; Andri Pranolo; Leonel Hernandez; Rafal Drezewski; Roman Voliansky; Mohamad Shanudin Zakaria; Bagus Muhammad Akbar; Shoffan Saifullah; Ahmad Taufiq Akbar; Rochmat Husaini; Heriyanto Heriyanto; Andiko Putro Suryotomo; Vynska Amalia Permadi; Sylvert Prian Tahalea. Institute of Electrical and Electronics Engineers Inc., 2019. p. 229-234 8987447 (Proceeding - 2019 5th International Conference on Science in Information Technology: Embracing Industry 4.0: Towards Innovation in Cyber Physical System, ICSITech 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Wound Classifications Of Breast Tissues with Electrical Impedance Spectroscopy (EIS)

T2 - 5th International Conference on Science in Information Technology, ICSITech 2019

AU - Arbawa, Yoke Kusuma

AU - Pisefty, R. Adhitya Dwi

AU - Bachtiar, Fitra A.

PY - 2019/10

Y1 - 2019/10

N2 - Deaths of people with breast diseases have reached 40% and are increasing every year. Breast Disease arises from wounds in breast tissue is breast cancer. Wounds of breast can be seen and discriminated the type of wound using Electrical Impedance Spectroscopy(EIS). The results of this EIS data can be used as an initial diagnosis before the doctor carries out treatment. This research tried to classify the types of wounds from breast tissue by using the Learning Vector Quantization (LVQ) method with the Genetic Algorithm (GA) to find out whether the solution provides the expected optimum results. The dataset we used for this study was very small which did not represent the existing class, with 106 data for 6 classes. The results of the comparison between LVQ and GA-LVQ obtained LVQ added by GA has higher accuracy values than LVQ with 73% accuracy and compared to LVQ, GA increased accuracy by ± 50%.

AB - Deaths of people with breast diseases have reached 40% and are increasing every year. Breast Disease arises from wounds in breast tissue is breast cancer. Wounds of breast can be seen and discriminated the type of wound using Electrical Impedance Spectroscopy(EIS). The results of this EIS data can be used as an initial diagnosis before the doctor carries out treatment. This research tried to classify the types of wounds from breast tissue by using the Learning Vector Quantization (LVQ) method with the Genetic Algorithm (GA) to find out whether the solution provides the expected optimum results. The dataset we used for this study was very small which did not represent the existing class, with 106 data for 6 classes. The results of the comparison between LVQ and GA-LVQ obtained LVQ added by GA has higher accuracy values than LVQ with 73% accuracy and compared to LVQ, GA increased accuracy by ± 50%.

KW - Breast tissue

KW - Classification

KW - Genetic Algorithm-Learning Vector Quantization

KW - Learning Vector Quantization

UR - https://www.scopus.com/pages/publications/85080954811

U2 - 10.1109/ICSITech46713.2019.8987447

DO - 10.1109/ICSITech46713.2019.8987447

M3 - Conference contribution

AN - SCOPUS:85080954811

T3 - Proceeding - 2019 5th International Conference on Science in Information Technology: Embracing Industry 4.0: Towards Innovation in Cyber Physical System, ICSITech 2019

SP - 229

EP - 234

BT - Proceeding - 2019 5th International Conference on Science in Information Technology

A2 - Pratomo, Awang Hendrianto

A2 - Pranolo, Andri

A2 - Hernandez, Leonel

A2 - Drezewski, Rafal

A2 - Voliansky, Roman

A2 - Zakaria, Mohamad Shanudin

A2 - Akbar, Bagus Muhammad

A2 - Saifullah, Shoffan

A2 - Akbar, Ahmad Taufiq

A2 - Husaini, Rochmat

A2 - Heriyanto, Heriyanto

A2 - Suryotomo, Andiko Putro

A2 - Permadi, Vynska Amalia

A2 - Tahalea, Sylvert Prian

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 23 October 2019 through 24 October 2019

ER -

Arbawa YK, Pisefty RAD, Bachtiar FA. Wound Classifications Of Breast Tissues with Electrical Impedance Spectroscopy (EIS): Comparison of LVQ and GA-LVQ. In Pratomo AH, Pranolo A, Hernandez L, Drezewski R, Voliansky R, Zakaria MS, Akbar BM, Saifullah S, Akbar AT, Husaini R, Heriyanto H, Suryotomo AP, Permadi VA, Tahalea SP, editors, Proceeding - 2019 5th International Conference on Science in Information Technology: Embracing Industry 4.0: Towards Innovation in Cyber Physical System, ICSITech 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 229-234. 8987447. (Proceeding - 2019 5th International Conference on Science in Information Technology: Embracing Industry 4.0: Towards Innovation in Cyber Physical System, ICSITech 2019). doi: 10.1109/ICSITech46713.2019.8987447

Wound Classifications Of Breast Tissues with Electrical Impedance Spectroscopy (EIS): Comparison of LVQ and GA-LVQ

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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