Empowering personalized medicine with big data and semantic web technology

Promises, challenges, and use cases

Maryam Panahiazar, Vahid Taslimitehrani, Ashutosh Jadhav, Jyotishman Pathak

Research output: Chapter in Book/Report/Conference proceedingConference contribution

33 Citations (Scopus)

Abstract

In healthcare, big data tools and technologies have the potential to create significant value by improving outcomes while lowering costs for each individual patient. Diagnostic images, genetic test results and biometric information are increasingly generated and stored in electronic health records presenting us with challenges in data that is by nature high volume, variety and velocity, thereby necessitating novel ways to store, manage and process big data. This presents an urgent need to develop new, scalable and expandable big data infrastructure and analytical methods that can enable healthcare providers access knowledge for the individual patient, yielding better decisions and outcomes. In this paper, we briefly discuss the nature of big data and the role of semantic web and data analysis for generating 'smart data' which offer actionable information that supports better decision for personalized medicine. In our view, the biggest challenge is to create a system that makes big data robust and smart for healthcare providers and patients that can lead to more effective clinical decision-making, improved health outcomes, and ultimately, managing the healthcare costs. We highlight some of the challenges in using big data and propose the need for a semantic data-driven environment to address them. We illustrate our vision with practical use cases, and discuss a path for empowering personalized medicine using big data and semantic web technology.

Original languageEnglish (US)
Title of host publicationProceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages790-795
Number of pages6
ISBN (Print)9781479956654
DOIs
StatePublished - Jan 7 2015
Event2nd IEEE International Conference on Big Data, IEEE Big Data 2014 - Washington, United States
Duration: Oct 27 2014Oct 30 2014

Other

Other2nd IEEE International Conference on Big Data, IEEE Big Data 2014
CountryUnited States
CityWashington
Period10/27/1410/30/14

Fingerprint

Semantic Web
Medicine
Health
Biometrics
Big data
Costs
Decision making
Semantics

Keywords

  • Big Data
  • Health Care
  • Personalized Medicine
  • Semantic Web
  • Smart Data

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

Cite this

Panahiazar, M., Taslimitehrani, V., Jadhav, A., & Pathak, J. (2015). Empowering personalized medicine with big data and semantic web technology: Promises, challenges, and use cases. In Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014 (pp. 790-795). [7004307] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.2014.7004307

Empowering personalized medicine with big data and semantic web technology : Promises, challenges, and use cases. / Panahiazar, Maryam; Taslimitehrani, Vahid; Jadhav, Ashutosh; Pathak, Jyotishman.

Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014. Institute of Electrical and Electronics Engineers Inc., 2015. p. 790-795 7004307.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Panahiazar, M, Taslimitehrani, V, Jadhav, A & Pathak, J 2015, Empowering personalized medicine with big data and semantic web technology: Promises, challenges, and use cases. in Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014., 7004307, Institute of Electrical and Electronics Engineers Inc., pp. 790-795, 2nd IEEE International Conference on Big Data, IEEE Big Data 2014, Washington, United States, 10/27/14. https://doi.org/10.1109/BigData.2014.7004307
Panahiazar M, Taslimitehrani V, Jadhav A, Pathak J. Empowering personalized medicine with big data and semantic web technology: Promises, challenges, and use cases. In Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014. Institute of Electrical and Electronics Engineers Inc. 2015. p. 790-795. 7004307 https://doi.org/10.1109/BigData.2014.7004307
Panahiazar, Maryam ; Taslimitehrani, Vahid ; Jadhav, Ashutosh ; Pathak, Jyotishman. / Empowering personalized medicine with big data and semantic web technology : Promises, challenges, and use cases. Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 790-795
@inproceedings{b985e83f764d4a6e8092f63f144d14ab,
title = "Empowering personalized medicine with big data and semantic web technology: Promises, challenges, and use cases",
abstract = "In healthcare, big data tools and technologies have the potential to create significant value by improving outcomes while lowering costs for each individual patient. Diagnostic images, genetic test results and biometric information are increasingly generated and stored in electronic health records presenting us with challenges in data that is by nature high volume, variety and velocity, thereby necessitating novel ways to store, manage and process big data. This presents an urgent need to develop new, scalable and expandable big data infrastructure and analytical methods that can enable healthcare providers access knowledge for the individual patient, yielding better decisions and outcomes. In this paper, we briefly discuss the nature of big data and the role of semantic web and data analysis for generating 'smart data' which offer actionable information that supports better decision for personalized medicine. In our view, the biggest challenge is to create a system that makes big data robust and smart for healthcare providers and patients that can lead to more effective clinical decision-making, improved health outcomes, and ultimately, managing the healthcare costs. We highlight some of the challenges in using big data and propose the need for a semantic data-driven environment to address them. We illustrate our vision with practical use cases, and discuss a path for empowering personalized medicine using big data and semantic web technology.",
keywords = "Big Data, Health Care, Personalized Medicine, Semantic Web, Smart Data",
author = "Maryam Panahiazar and Vahid Taslimitehrani and Ashutosh Jadhav and Jyotishman Pathak",
year = "2015",
month = "1",
day = "7",
doi = "10.1109/BigData.2014.7004307",
language = "English (US)",
isbn = "9781479956654",
pages = "790--795",
booktitle = "Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Empowering personalized medicine with big data and semantic web technology

T2 - Promises, challenges, and use cases

AU - Panahiazar, Maryam

AU - Taslimitehrani, Vahid

AU - Jadhav, Ashutosh

AU - Pathak, Jyotishman

PY - 2015/1/7

Y1 - 2015/1/7

N2 - In healthcare, big data tools and technologies have the potential to create significant value by improving outcomes while lowering costs for each individual patient. Diagnostic images, genetic test results and biometric information are increasingly generated and stored in electronic health records presenting us with challenges in data that is by nature high volume, variety and velocity, thereby necessitating novel ways to store, manage and process big data. This presents an urgent need to develop new, scalable and expandable big data infrastructure and analytical methods that can enable healthcare providers access knowledge for the individual patient, yielding better decisions and outcomes. In this paper, we briefly discuss the nature of big data and the role of semantic web and data analysis for generating 'smart data' which offer actionable information that supports better decision for personalized medicine. In our view, the biggest challenge is to create a system that makes big data robust and smart for healthcare providers and patients that can lead to more effective clinical decision-making, improved health outcomes, and ultimately, managing the healthcare costs. We highlight some of the challenges in using big data and propose the need for a semantic data-driven environment to address them. We illustrate our vision with practical use cases, and discuss a path for empowering personalized medicine using big data and semantic web technology.

AB - In healthcare, big data tools and technologies have the potential to create significant value by improving outcomes while lowering costs for each individual patient. Diagnostic images, genetic test results and biometric information are increasingly generated and stored in electronic health records presenting us with challenges in data that is by nature high volume, variety and velocity, thereby necessitating novel ways to store, manage and process big data. This presents an urgent need to develop new, scalable and expandable big data infrastructure and analytical methods that can enable healthcare providers access knowledge for the individual patient, yielding better decisions and outcomes. In this paper, we briefly discuss the nature of big data and the role of semantic web and data analysis for generating 'smart data' which offer actionable information that supports better decision for personalized medicine. In our view, the biggest challenge is to create a system that makes big data robust and smart for healthcare providers and patients that can lead to more effective clinical decision-making, improved health outcomes, and ultimately, managing the healthcare costs. We highlight some of the challenges in using big data and propose the need for a semantic data-driven environment to address them. We illustrate our vision with practical use cases, and discuss a path for empowering personalized medicine using big data and semantic web technology.

KW - Big Data

KW - Health Care

KW - Personalized Medicine

KW - Semantic Web

KW - Smart Data

UR - http://www.scopus.com/inward/record.url?scp=84921714097&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84921714097&partnerID=8YFLogxK

U2 - 10.1109/BigData.2014.7004307

DO - 10.1109/BigData.2014.7004307

M3 - Conference contribution

SN - 9781479956654

SP - 790

EP - 795

BT - Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014

PB - Institute of Electrical and Electronics Engineers Inc.

ER -