Mining Personal Health Index from Annual Geriatric Medical Examinations

Ling Chen; Xue Li; Sen Wang; Hsiao Yun Hu; Nicole Huang; Quan Z. Sheng; Mohamed Sharaf

doi:10.1109/ICDM.2014.32

Mining Personal Health Index from Annual Geriatric Medical Examinations

Ling Chen
, Xue Li
, Sen Wang
, Hsiao Yun Hu
, Nicole Huang
, Quan Z. Sheng
, Mohamed Sharaf

Institute of Hospital and Health Care Administration

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

12 Scopus citations

Abstract

People take regular medical examinations mostly not for discovering diseases but for having a peace of mind regarding their health status. Therefore, it is important to give them an overall feedback with respect to all the health indicators that have been ranked against the whole population. In this paper, we propose a framework of mining Personal Health Index (PHI) from a large and comprehensive geriatric medical examination (GME) dataset. We define PHI as an overall score of personal health status based on a complement probability of health risks. The health risks are calculated using the information from the cause of death (COD) dataset that is linked to the GME dataset. Especially, the highest health risk is revealed in the cases of people who had been taking GME for some years and then passed away for medical reasons. The proposed framework consists of methods in data pre-processing, feature extraction and selection, and model selection. The effectiveness of the proposed framework is validated by a set of comprehensive experiments based on the records of 102,258 participants. As the first of this kind, our work provides a baseline for further research.

Original language	English
Title of host publication	Proceedings - 14th IEEE International Conference on Data Mining, ICDM 2014
Editors	Ravi Kumar, Hannu Toivonen, Jian Pei, Joshua Zhexue Huang, Xindong Wu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	761-766
Number of pages	6
Edition	January
ISBN (Electronic)	9781479943029
DOIs	https://doi.org/10.1109/ICDM.2014.32
State	Published - 1 Jan 2014
Event	14th IEEE International Conference on Data Mining, ICDM 2014 - Shenzhen, China Duration: 14 Dec 2014 → 17 Dec 2014

Publication series

Name	Proceedings - IEEE International Conference on Data Mining, ICDM
Number	January
Volume	2015-January
ISSN (Print)	1550-4786

Conference

Conference	14th IEEE International Conference on Data Mining, ICDM 2014
Country/Territory	China
City	Shenzhen
Period	14/12/14 → 17/12/14

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Personal Health Index
geriatric medical examination

Access to Document

10.1109/ICDM.2014.32

Cite this

Chen, L., Li, X., Wang, S., Hu, H. Y., Huang, N., Sheng, Q. Z., & Sharaf, M. (2014). Mining Personal Health Index from Annual Geriatric Medical Examinations. In R. Kumar, H. Toivonen, J. Pei, J. Zhexue Huang, & X. Wu (Eds.), Proceedings - 14th IEEE International Conference on Data Mining, ICDM 2014 (January ed., pp. 761-766). Article 7023397 (Proceedings - IEEE International Conference on Data Mining, ICDM; Vol. 2015-January, No. January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDM.2014.32

Chen, Ling ; Li, Xue ; Wang, Sen et al. / Mining Personal Health Index from Annual Geriatric Medical Examinations. Proceedings - 14th IEEE International Conference on Data Mining, ICDM 2014. editor / Ravi Kumar ; Hannu Toivonen ; Jian Pei ; Joshua Zhexue Huang ; Xindong Wu. January. ed. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 761-766 (Proceedings - IEEE International Conference on Data Mining, ICDM; January).

@inproceedings{2747acc22f5b442d8b8e54797d0aaad5,

title = "Mining Personal Health Index from Annual Geriatric Medical Examinations",

abstract = "People take regular medical examinations mostly not for discovering diseases but for having a peace of mind regarding their health status. Therefore, it is important to give them an overall feedback with respect to all the health indicators that have been ranked against the whole population. In this paper, we propose a framework of mining Personal Health Index (PHI) from a large and comprehensive geriatric medical examination (GME) dataset. We define PHI as an overall score of personal health status based on a complement probability of health risks. The health risks are calculated using the information from the cause of death (COD) dataset that is linked to the GME dataset. Especially, the highest health risk is revealed in the cases of people who had been taking GME for some years and then passed away for medical reasons. The proposed framework consists of methods in data pre-processing, feature extraction and selection, and model selection. The effectiveness of the proposed framework is validated by a set of comprehensive experiments based on the records of 102,258 participants. As the first of this kind, our work provides a baseline for further research.",

keywords = "Personal Health Index, geriatric medical examination",

author = "Ling Chen and Xue Li and Sen Wang and Hu, \{Hsiao Yun\} and Nicole Huang and Sheng, \{Quan Z.\} and Mohamed Sharaf",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 14th IEEE International Conference on Data Mining, ICDM 2014 ; Conference date: 14-12-2014 Through 17-12-2014",

year = "2014",

month = jan,

day = "1",

doi = "10.1109/ICDM.2014.32",

language = "English",

series = "Proceedings - IEEE International Conference on Data Mining, ICDM",

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

number = "January",

pages = "761--766",

editor = "Ravi Kumar and Hannu Toivonen and Jian Pei and \{Zhexue Huang\}, Joshua and Xindong Wu",

booktitle = "Proceedings - 14th IEEE International Conference on Data Mining, ICDM 2014",

address = "美國",

edition = "January",

}

Chen, L, Li, X, Wang, S, Hu, HY, Huang, N, Sheng, QZ & Sharaf, M 2014, Mining Personal Health Index from Annual Geriatric Medical Examinations. in R Kumar, H Toivonen, J Pei, J Zhexue Huang & X Wu (eds), Proceedings - 14th IEEE International Conference on Data Mining, ICDM 2014. January edn, 7023397, Proceedings - IEEE International Conference on Data Mining, ICDM, no. January, vol. 2015-January, Institute of Electrical and Electronics Engineers Inc., pp. 761-766, 14th IEEE International Conference on Data Mining, ICDM 2014, Shenzhen, China, 14/12/14. https://doi.org/10.1109/ICDM.2014.32

Mining Personal Health Index from Annual Geriatric Medical Examinations. / Chen, Ling; Li, Xue; Wang, Sen et al.
Proceedings - 14th IEEE International Conference on Data Mining, ICDM 2014. ed. / Ravi Kumar; Hannu Toivonen; Jian Pei; Joshua Zhexue Huang; Xindong Wu. January. ed. Institute of Electrical and Electronics Engineers Inc., 2014. p. 761-766 7023397 (Proceedings - IEEE International Conference on Data Mining, ICDM; Vol. 2015-January, No. January).

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

TY - GEN

T1 - Mining Personal Health Index from Annual Geriatric Medical Examinations

AU - Chen, Ling

AU - Li, Xue

AU - Wang, Sen

AU - Hu, Hsiao Yun

AU - Huang, Nicole

AU - Sheng, Quan Z.

AU - Sharaf, Mohamed

PY - 2014/1/1

Y1 - 2014/1/1

N2 - People take regular medical examinations mostly not for discovering diseases but for having a peace of mind regarding their health status. Therefore, it is important to give them an overall feedback with respect to all the health indicators that have been ranked against the whole population. In this paper, we propose a framework of mining Personal Health Index (PHI) from a large and comprehensive geriatric medical examination (GME) dataset. We define PHI as an overall score of personal health status based on a complement probability of health risks. The health risks are calculated using the information from the cause of death (COD) dataset that is linked to the GME dataset. Especially, the highest health risk is revealed in the cases of people who had been taking GME for some years and then passed away for medical reasons. The proposed framework consists of methods in data pre-processing, feature extraction and selection, and model selection. The effectiveness of the proposed framework is validated by a set of comprehensive experiments based on the records of 102,258 participants. As the first of this kind, our work provides a baseline for further research.

AB - People take regular medical examinations mostly not for discovering diseases but for having a peace of mind regarding their health status. Therefore, it is important to give them an overall feedback with respect to all the health indicators that have been ranked against the whole population. In this paper, we propose a framework of mining Personal Health Index (PHI) from a large and comprehensive geriatric medical examination (GME) dataset. We define PHI as an overall score of personal health status based on a complement probability of health risks. The health risks are calculated using the information from the cause of death (COD) dataset that is linked to the GME dataset. Especially, the highest health risk is revealed in the cases of people who had been taking GME for some years and then passed away for medical reasons. The proposed framework consists of methods in data pre-processing, feature extraction and selection, and model selection. The effectiveness of the proposed framework is validated by a set of comprehensive experiments based on the records of 102,258 participants. As the first of this kind, our work provides a baseline for further research.

KW - Personal Health Index

KW - geriatric medical examination

UR - https://www.scopus.com/pages/publications/84936940781

U2 - 10.1109/ICDM.2014.32

DO - 10.1109/ICDM.2014.32

M3 - Conference contribution

AN - SCOPUS:84936940781

T3 - Proceedings - IEEE International Conference on Data Mining, ICDM

SP - 761

EP - 766

BT - Proceedings - 14th IEEE International Conference on Data Mining, ICDM 2014

A2 - Kumar, Ravi

A2 - Toivonen, Hannu

A2 - Pei, Jian

A2 - Zhexue Huang, Joshua

A2 - Wu, Xindong

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 14th IEEE International Conference on Data Mining, ICDM 2014

Y2 - 14 December 2014 through 17 December 2014

ER -

Chen L, Li X, Wang S, Hu HY, Huang N, Sheng QZ et al. Mining Personal Health Index from Annual Geriatric Medical Examinations. In Kumar R, Toivonen H, Pei J, Zhexue Huang J, Wu X, editors, Proceedings - 14th IEEE International Conference on Data Mining, ICDM 2014. January ed. Institute of Electrical and Electronics Engineers Inc. 2014. p. 761-766. 7023397. (Proceedings - IEEE International Conference on Data Mining, ICDM; January). doi: 10.1109/ICDM.2014.32

Mining Personal Health Index from Annual Geriatric Medical Examinations

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this