NDLI: Multi-patient learning increases accuracy for Subthalamic nucleus identification in deep brain stimulation

Content Provider	IEEE Xplore Digital Library
Author	Vargas Cardona, H.D. Orozco, A.A. Alvarez, M.A.
Copyright Year	2012
Description	Author affiliation: Dept. of Electr. Eng., Univ. Tecnol. de Pereira, Pereira, Colombia (Vargas Cardona, H.D.; Orozco, A.A.; Alvarez, M.A.)
Abstract	Establishing the exact position of basal ganglia is key in several brain surgeries, particularly in deep brain stimulation for patients suffering from Parkinson's disease. There have been recent attempts to introduce automatic systems with the ability to localize, with high accuracy, specific brain regions. These systems usually follow the classical supervised learning paradigm, in which training data from different patients are employed to construct a classifier that is patient-independent. In this paper, we show how by sharing information from different patients, it is possible to increase accuracy for targeting the Subthalamic Nucleus. We do this in the context of multi-task learning, where different but related tasks are used simultaneously to leverage the performance of a learning system. Results show that the multitask framework can outperform the traditional patient-independent scenario in two different real datasets.
Sponsorship	IEEE Eng. Medicine Biol. Soc.
Starting Page	4341
Ending Page	4344
File Size	377945
Page Count	4
File Format	PDF
ISBN	9781424441198
ISSN	1557170X
e-ISBN	9781457717871
DOI	10.1109/EMBC.2012.6346927
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Accuracy Gaussian processes Support vector machines Training Databases Machine learning Standards
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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