Survival and Quality of Life of Cancer Patients
In this research project we are developing tools
that will help doctors and cancer patients make better
informed decisions about courses of treatment.
Our work so far has focused on pancreatic cancer, which has
an especially high mortality rate and low life expectancy.
Survival of some patients may be extended through surgery
(Whipple procedure). However, this procedure is very
traumatic and has a lengthy recovery time. Thus, the
decision to operate will have a significant impact on
quality of life of the patient and it is important
that the decision take into account the best available
forecasting techniques. Our current work involves a
combination of machine learning and more traditional
multivariate regression for improved forecasting.
Plans include developing machine learning models
that will aid understanding of the factors that
affect survival and quality of life, with the aim
of improving both.
Publications (asterisks denote student co-authors)
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S. Floyd*, C. Ruiz, S. A. Alvarez, J. Tseng, and G. Whalen.
"Prediction of Pancreatic Cancer Survival through Automated Selection of
Predictive Models", in Biomedical Engineering Systems and Technologies, Third International Joint Conference, BIOSTEC 2010, Valencia, Spain, January 2010, Revised Selected Papers (Ana Fred, Joaquim Filipe and Hugo Gamboa, eds.),
Communications in Computer and Information Science, Volume 127,
Springer, 2011, 29-43
ISBN: 978-3-642-18471-0
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J. Hayward*, S. A. Alvarez, C. Ruiz, M. Sullivan, J. Tseng, and G. Whalen.
"Machine Learning of Clinical Performance in a Pancreatic Cancer Database",
Artificial Intelligence in Medicine, special issue on Data Mining
Approaches to the Study of Disease Genes and Proteins (Sun Kim, ed.),
vol. 49, issue 3, July 2010, 187-195
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S. Floyd*, C. Ruiz, S. A. Alvarez, J. Tseng, and G. Whalen.
"Model Selection Meta-Learning for the Prognosis of Pancreatic Cancer",
full paper,
Third International Conference on Health Informatics (HEALTHINF 2010),
Valencia, Spain, Jan. 20-23, 2010
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J. Hayward*, S. A. Alvarez, C. Ruiz, M. Sullivan, J. Tseng, and G. Whalen.
"Knowledge Discovery in Clinical Performance of Cancer Patients",
regular paper (acceptance rate: 38/156 = 24.4%),
2008 IEEE International Conference on Bioinformatics and Biomedicine,
Philadelphia, PA, USA, Nov. 3-5, 2008
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S. Floyd*, S.A. Alvarez, C. Ruiz, J. Hayward*, M. Sullivan, J. Tseng,
and G. Whalen.
"Improved Survival Prediction for Pancreatic Cancer using Machine Learning
and Regression", accepted for presentation at the
Society for the Surgery of the Alimentary Tract 48th Annual Meeting
(SSAT 2007), in conjunction with Digestive Disease Week (DDW 2007),
Washington, DC, USA, May 19-23, 2007
-
J. Hayward*, S.A. Alvarez, C. Ruiz, J. Tseng, M. Sullivan, and G. Whalen.
"Survival of Pancreatic Cancer Patients Predicted using Machine Learning
Techniques", accepted for presentation at the
Society of Surgical Oncology 60th Annual Cancer Symposium,
Washington, DC, USA, March 15-18, 2007
Project Personnel
Faculty
- Sergio A. Alvarez, Ph.D. (Boston College)
- Carolina Ruiz, Ph.D. (Worcester Polytechnic Institute)
- Giles Whalen, M.D. (U. of Massachusetts Medical School)
- Jennifer Tseng, M.D. (U. of Massachusetts Medical School)
Alumni
- Stuart Floyd, M.S.
- John Hayward, M.S. (currently at Raytheon)