New Cancer Treatment Evaluation through Big Data Analytics

Gangmin Li; Jianze Gu; Xuming Bai

doi:10.1109/ICSAI.2018.8599466

New Cancer Treatment Evaluation through Big Data Analytics

Gangmin Li
, Jianze Gu
, Xuming Bai

Xi'an Jiaotong-Liverpool University

Xi'an Jiaotong-Liverpool University
The second affiliated Hospital of Soochow University Suzhou

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

Abstract

Cancer plays a leading role in causing morbidity and mortality worldwide. Several treatments have been developed and practiced for fighting against cancer. Totally Implantable Venous Access Port Drug Supply (TIVAPDS) treatment is a new method utilizing Totally Implantable Venous Access Port (TIVAP) delivery method, which is one kind of Intrathecal Drug Delivery System (IDD) with lower side effects, to increase patient's quality of life. This paper reports our study aiming to evaluate the effectiveness of TIVAPDS treatment in order to make contributions to generalize this treatment in China. Our data samples come from The Second Affiliated Hospital of Suzhou University, a forerunner of TIVAPDS practices in China and with patients' agreement. The data statistics summary results and the relationships between each two identified attributes are analyzed. Based on the results, 2 predictive models utilizing C4.5 decision tree and logistic regression algorithms are adopted for prediction. The results are used as reference to assess individual treatment cases, so that the effectiveness of the treatment can be achieved and if possible, to improve the efficiency of TIVAPDS treatment.

Original language	English
Title of host publication	2018 5th International Conference on Systems and Informatics, ICSAI 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	484-489
Number of pages	6
ISBN (Electronic)	9781728101200
DOIs	https://doi.org/10.1109/ICSAI.2018.8599466
Publication status	Published - 2 Jan 2019
Event	5th International Conference on Systems and Informatics, ICSAI 2018 - Nanjing, China Duration: 10 Nov 2018 → 12 Nov 2018

Publication series

Name	2018 5th International Conference on Systems and Informatics, ICSAI 2018

Conference

Conference	5th International Conference on Systems and Informatics, ICSAI 2018
Country/Territory	China
City	Nanjing
Period	10/11/18 → 12/11/18

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Big Data analysis
C4.5 decision tree
Effectiveness
Length of stay (LOS)
Logistic regression.
Prognostic prediction model
TIVAPDS

Access to Document

10.1109/ICSAI.2018.8599466

Cite this

Li, G., Gu, J., & Bai, X. (2019). New Cancer Treatment Evaluation through Big Data Analytics. In 2018 5th International Conference on Systems and Informatics, ICSAI 2018 (pp. 484-489). Article 8599466 (2018 5th International Conference on Systems and Informatics, ICSAI 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSAI.2018.8599466

@inproceedings{c6df2be6149c450f9be7d67821ee02fc,

title = "New Cancer Treatment Evaluation through Big Data Analytics",

abstract = "Cancer plays a leading role in causing morbidity and mortality worldwide. Several treatments have been developed and practiced for fighting against cancer. Totally Implantable Venous Access Port Drug Supply (TIVAPDS) treatment is a new method utilizing Totally Implantable Venous Access Port (TIVAP) delivery method, which is one kind of Intrathecal Drug Delivery System (IDD) with lower side effects, to increase patient's quality of life. This paper reports our study aiming to evaluate the effectiveness of TIVAPDS treatment in order to make contributions to generalize this treatment in China. Our data samples come from The Second Affiliated Hospital of Suzhou University, a forerunner of TIVAPDS practices in China and with patients' agreement. The data statistics summary results and the relationships between each two identified attributes are analyzed. Based on the results, 2 predictive models utilizing C4.5 decision tree and logistic regression algorithms are adopted for prediction. The results are used as reference to assess individual treatment cases, so that the effectiveness of the treatment can be achieved and if possible, to improve the efficiency of TIVAPDS treatment.",

keywords = "Big Data analysis, C4.5 decision tree, Effectiveness, Length of stay (LOS), Logistic regression., Prognostic prediction model, TIVAPDS",

author = "Gangmin Li and Jianze Gu and Xuming Bai",

note = "Funding Information: ACKNOWLEDGMENT This research project was supported by the fund provided by the Research Institute of Big Data Analytics (RIBDA), Xi{\textquoteright}an Jiaotong-Liverpool University and The 2nd Affiliated Hospital of Suzhou University. Publisher Copyright: {\textcopyright} 2018 IEEE.; 5th International Conference on Systems and Informatics, ICSAI 2018 ; Conference date: 10-11-2018 Through 12-11-2018",

year = "2019",

month = jan,

day = "2",

doi = "10.1109/ICSAI.2018.8599466",

language = "English",

series = "2018 5th International Conference on Systems and Informatics, ICSAI 2018",

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

pages = "484--489",

booktitle = "2018 5th International Conference on Systems and Informatics, ICSAI 2018",

}

Li, G, Gu, J & Bai, X 2019, New Cancer Treatment Evaluation through Big Data Analytics. in 2018 5th International Conference on Systems and Informatics, ICSAI 2018., 8599466, 2018 5th International Conference on Systems and Informatics, ICSAI 2018, Institute of Electrical and Electronics Engineers Inc., pp. 484-489, 5th International Conference on Systems and Informatics, ICSAI 2018, Nanjing, China, 10/11/18. https://doi.org/10.1109/ICSAI.2018.8599466

New Cancer Treatment Evaluation through Big Data Analytics. / Li, Gangmin; Gu, Jianze; Bai, Xuming.
2018 5th International Conference on Systems and Informatics, ICSAI 2018. Institute of Electrical and Electronics Engineers Inc., 2019. p. 484-489 8599466 (2018 5th International Conference on Systems and Informatics, ICSAI 2018).

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

TY - GEN

T1 - New Cancer Treatment Evaluation through Big Data Analytics

AU - Li, Gangmin

AU - Gu, Jianze

AU - Bai, Xuming

N1 - Funding Information: ACKNOWLEDGMENT This research project was supported by the fund provided by the Research Institute of Big Data Analytics (RIBDA), Xi’an Jiaotong-Liverpool University and The 2nd Affiliated Hospital of Suzhou University. Publisher Copyright: © 2018 IEEE.

PY - 2019/1/2

Y1 - 2019/1/2

N2 - Cancer plays a leading role in causing morbidity and mortality worldwide. Several treatments have been developed and practiced for fighting against cancer. Totally Implantable Venous Access Port Drug Supply (TIVAPDS) treatment is a new method utilizing Totally Implantable Venous Access Port (TIVAP) delivery method, which is one kind of Intrathecal Drug Delivery System (IDD) with lower side effects, to increase patient's quality of life. This paper reports our study aiming to evaluate the effectiveness of TIVAPDS treatment in order to make contributions to generalize this treatment in China. Our data samples come from The Second Affiliated Hospital of Suzhou University, a forerunner of TIVAPDS practices in China and with patients' agreement. The data statistics summary results and the relationships between each two identified attributes are analyzed. Based on the results, 2 predictive models utilizing C4.5 decision tree and logistic regression algorithms are adopted for prediction. The results are used as reference to assess individual treatment cases, so that the effectiveness of the treatment can be achieved and if possible, to improve the efficiency of TIVAPDS treatment.

AB - Cancer plays a leading role in causing morbidity and mortality worldwide. Several treatments have been developed and practiced for fighting against cancer. Totally Implantable Venous Access Port Drug Supply (TIVAPDS) treatment is a new method utilizing Totally Implantable Venous Access Port (TIVAP) delivery method, which is one kind of Intrathecal Drug Delivery System (IDD) with lower side effects, to increase patient's quality of life. This paper reports our study aiming to evaluate the effectiveness of TIVAPDS treatment in order to make contributions to generalize this treatment in China. Our data samples come from The Second Affiliated Hospital of Suzhou University, a forerunner of TIVAPDS practices in China and with patients' agreement. The data statistics summary results and the relationships between each two identified attributes are analyzed. Based on the results, 2 predictive models utilizing C4.5 decision tree and logistic regression algorithms are adopted for prediction. The results are used as reference to assess individual treatment cases, so that the effectiveness of the treatment can be achieved and if possible, to improve the efficiency of TIVAPDS treatment.

KW - Big Data analysis

KW - C4.5 decision tree

KW - Effectiveness

KW - Length of stay (LOS)

KW - Logistic regression.

KW - Prognostic prediction model

KW - TIVAPDS

UR - https://www.scopus.com/pages/publications/85061508015

U2 - 10.1109/ICSAI.2018.8599466

DO - 10.1109/ICSAI.2018.8599466

M3 - Conference Proceeding

AN - SCOPUS:85061508015

T3 - 2018 5th International Conference on Systems and Informatics, ICSAI 2018

SP - 484

EP - 489

BT - 2018 5th International Conference on Systems and Informatics, ICSAI 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 5th International Conference on Systems and Informatics, ICSAI 2018

Y2 - 10 November 2018 through 12 November 2018

ER -

New Cancer Treatment Evaluation through Big Data Analytics

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this