Porting a cancer treatment prediction to a mobile device.

Tim Gegg-Harrison, Mingrui Zhang, Nan Meng, Zhifii Sun, Ping Yang

Research output: Contribution to journalArticle

Abstract

The Lung Cancer Survivability Prediction Tool (LCSPT) is a web-based system that predicts the survival possibility of a lung cancer patient based on the status of the patient and the treatments provided. In order to make the LCSPT more accessible and convenient to doctors working in a clinical setting, we have developed a new interface for mobile devices. The display size along with wireless data transfer speeds pose the most significant challenges to porting a software application to a mobile device. We have addressed these issues by redefining the interface and limiting the amount of data that is required. The resultant tool provides doctors with the flexibility of mobility while maintaining the effectiveness of the desktop version of the LCSPT.

Original languageEnglish (US)
Pages (from-to)6218-6221
Number of pages4
JournalConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
StatePublished - 2009
Externally publishedYes

Fingerprint

Oncology
Mobile devices
Lung Neoplasms
Equipment and Supplies
Neoplasms
Therapeutics
Data transfer
Application programs
Software
Display devices
Survival

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Cite this

@article{b54462a7f0d044859b7c9d6c142acda3,
title = "Porting a cancer treatment prediction to a mobile device.",
abstract = "The Lung Cancer Survivability Prediction Tool (LCSPT) is a web-based system that predicts the survival possibility of a lung cancer patient based on the status of the patient and the treatments provided. In order to make the LCSPT more accessible and convenient to doctors working in a clinical setting, we have developed a new interface for mobile devices. The display size along with wireless data transfer speeds pose the most significant challenges to porting a software application to a mobile device. We have addressed these issues by redefining the interface and limiting the amount of data that is required. The resultant tool provides doctors with the flexibility of mobility while maintaining the effectiveness of the desktop version of the LCSPT.",
author = "Tim Gegg-Harrison and Mingrui Zhang and Nan Meng and Zhifii Sun and Ping Yang",
year = "2009",
language = "English (US)",
pages = "6218--6221",
journal = "Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference",
issn = "1557-170X",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - JOUR

T1 - Porting a cancer treatment prediction to a mobile device.

AU - Gegg-Harrison, Tim

AU - Zhang, Mingrui

AU - Meng, Nan

AU - Sun, Zhifii

AU - Yang, Ping

PY - 2009

Y1 - 2009

N2 - The Lung Cancer Survivability Prediction Tool (LCSPT) is a web-based system that predicts the survival possibility of a lung cancer patient based on the status of the patient and the treatments provided. In order to make the LCSPT more accessible and convenient to doctors working in a clinical setting, we have developed a new interface for mobile devices. The display size along with wireless data transfer speeds pose the most significant challenges to porting a software application to a mobile device. We have addressed these issues by redefining the interface and limiting the amount of data that is required. The resultant tool provides doctors with the flexibility of mobility while maintaining the effectiveness of the desktop version of the LCSPT.

AB - The Lung Cancer Survivability Prediction Tool (LCSPT) is a web-based system that predicts the survival possibility of a lung cancer patient based on the status of the patient and the treatments provided. In order to make the LCSPT more accessible and convenient to doctors working in a clinical setting, we have developed a new interface for mobile devices. The display size along with wireless data transfer speeds pose the most significant challenges to porting a software application to a mobile device. We have addressed these issues by redefining the interface and limiting the amount of data that is required. The resultant tool provides doctors with the flexibility of mobility while maintaining the effectiveness of the desktop version of the LCSPT.

UR - http://www.scopus.com/inward/record.url?scp=84903871128&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84903871128&partnerID=8YFLogxK

M3 - Article

C2 - 19965083

SP - 6218

EP - 6221

JO - Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference

JF - Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference

SN - 1557-170X

ER -