Article

Towards better than human capability in diagnosing prostate cancer using infrared spectroscopic imaging

Authors:

Rohit BhargavaAuthors Info & Claims

GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation

Pages 2098 - 2105

https://doi.org/10.1145/1276958.1277366

Published: 07 July 2007 Publication History

Abstract

Cancer diagnosis is essentially a human task. Almost universally, the process requires the extraction of tissue (biopsy) and examination of its microstructure by a human. To improve diagnoses based on limited and inconsistent morphologic knowledge, a new approach has recently been proposed that uses molecular spectroscopic imaging to utilize microscopic chemical composition for diagnoses. In contrast to visible imaging, the approach results in very large data sets as each pixel contains the entire molecular vibrational spectroscopy data from all chemical species. Here, we propose data handling and analysis strategies to allow computer-based diagnosis of human prostate cancer by applying a novel genetics-based machine learning technique ({\tt NAX). We apply this technique to demonstrate both fast learning and accurate classification that, additionally, scales well with parallelization. Preliminary results demonstrate that this approach can improve current clinical practice in diagnosing prostate cancer.

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Cited By

Reihanisaransari RGajjela CWu XIshrak RZhong YMayerich DBerisha SReddy R(2024)Cervical Cancer Tissue Analysis Using Photothermal Midinfrared Spectroscopic ImagingChemical & Biomedical Imaging10.1021/cbmi.4c00031Online publication date: 31-Jul-2024
https://doi.org/10.1021/cbmi.4c00031
Ferjani RRejeb LSaid L(2020)Cooperative Reinforcement Multi-Agent Learning System for Sleep Stages Classification2020 International Multi-Conference on: “Organization of Knowledge and Advanced Technologies” (OCTA)10.1109/OCTA49274.2020.9151700(1-8)Online publication date: Feb-2020
https://doi.org/10.1109/OCTA49274.2020.9151700
Ferjani RRejeb LSaid L(2020)Unsupervised Sleep Stages Classification Based on Physiological SignalsAdvances in Practical Applications of Agents, Multi-Agent Systems, and Trustworthiness. The PAAMS Collection10.1007/978-3-030-49778-1_11(134-145)Online publication date: 15-Jun-2020
https://doi.org/10.1007/978-3-030-49778-1_11
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Index Terms

Towards better than human capability in diagnosing prostate cancer using infrared spectroscopic imaging
1. Applied computing
  1. Life and medical sciences
    1. Health care information systems
2. Computing methodologies
  1. Machine learning

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cover image ACM Conferences

GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation

July 2007

2313 pages

ISBN:9781595936974

DOI:10.1145/1276958

General Chair:
Hod Lipson
Cornell University, USA

Copyright © 2007 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 07 July 2007

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GECCO07: Genetic and Evolutionary Computation Conference

July 7 - 11, 2007

London, England

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GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;

Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Reihanisaransari RGajjela CWu XIshrak RZhong YMayerich DBerisha SReddy R(2024)Cervical Cancer Tissue Analysis Using Photothermal Midinfrared Spectroscopic ImagingChemical & Biomedical Imaging10.1021/cbmi.4c00031Online publication date: 31-Jul-2024
https://doi.org/10.1021/cbmi.4c00031
Ferjani RRejeb LSaid L(2020)Cooperative Reinforcement Multi-Agent Learning System for Sleep Stages Classification2020 International Multi-Conference on: “Organization of Knowledge and Advanced Technologies” (OCTA)10.1109/OCTA49274.2020.9151700(1-8)Online publication date: Feb-2020
https://doi.org/10.1109/OCTA49274.2020.9151700
Ferjani RRejeb LSaid L(2020)Unsupervised Sleep Stages Classification Based on Physiological SignalsAdvances in Practical Applications of Agents, Multi-Agent Systems, and Trustworthiness. The PAAMS Collection10.1007/978-3-030-49778-1_11(134-145)Online publication date: 15-Jun-2020
https://doi.org/10.1007/978-3-030-49778-1_11
Sammouda RAboalsamh HSaeed F(2015)Comparison between K mean and fuzzy C-mean methods for segmentation of near infrared fluorescent image for diagnosing prostate cancerInternational Conference on Computer Vision and Image Analysis Applications10.1109/ICCVIA.2015.7351905(1-6)Online publication date: Jan-2015
https://doi.org/10.1109/ICCVIA.2015.7351905
Sammouda RWang XBasilion J(2015)Hopfield Neural Network for the segmentation of Near Infrared Fluorescent images for diagnosing prostate cancer2015 6th International Conference on Information and Communication Systems (ICICS)10.1109/IACS.2015.7103212(111-118)Online publication date: Apr-2015
https://doi.org/10.1109/IACS.2015.7103212
Urbanowicz RMoore J(2014)Learning Classifier Systems: The Rise of Genetics-Based Machine Learning in Biomedical Data MiningMethods in Biomedical Informatics10.1016/B978-0-12-401678-1.00009-9(265-311)Online publication date: 2014
https://doi.org/10.1016/B978-0-12-401678-1.00009-9
Hemberg EVeeramachaneni KDernoncourt FWagy MO'Reilly UAlba E(2013)Efficient training set use for blood pressure prediction in a large scale learning classifier systemProceedings of the 15th annual conference companion on Genetic and evolutionary computation10.1145/2464576.2482705(1267-1274)Online publication date: 6-Jul-2013
https://dl.acm.org/doi/10.1145/2464576.2482705
Moreno-Torres JLlorí XGoldberg DBhargava R(2013)Repairing fractures between data using genetic programming-based feature extractionInformation Sciences: an International Journal10.1016/j.ins.2010.09.018222(805-823)Online publication date: 1-Feb-2013
https://dl.acm.org/doi/10.1016/j.ins.2010.09.018
Franco MKrasnogor NBacardit J(2013)GAssist vs. BioHELSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-013-1016-817:6(953-981)Online publication date: 1-Jun-2013
https://dl.acm.org/doi/10.1007/s00500-013-1016-8
Urbanowicz RGranizo-Mackenzie AMoore J(2012)An analysis pipeline with statistical and visualization-guided knowledge discovery for Michigan-style learning classifier systemsIEEE Computational Intelligence Magazine10.1109/MCI.2012.22151247:4(35-45)Online publication date: 1-Nov-2012
https://dl.acm.org/doi/10.1109/MCI.2012.2215124
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