News
[2011/10/27] The code of the clinical evidence detector is now available under an Apache License V2.0 as a SourceForge project.
[2011/06/31] The complete corpus based on the clinical inquiries of the Journal of Family Practice is now available. Contact Diego Molla for further details. Include a short introduction of yourself and what you plan to do with the corpus.
Diego Mollá Aliod
Natural Language Processing of Medical Texts |
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This project focuses on the application of natural language processing techniques on medical texts. We pay special emphasis on finding methods to help the practice of evidence based medicine.
Resources
Members
- Diego Mollá (project director and chief investigator)
- Cécile Paris (partner investigator, CSIRO ICT Centre)
- Abeed Sarker (PhD student)
- Sara Faisal Shash (Masters student)
Past Members
The following people had done significant work for the project, leading to publication.
- Maria Elena Santiago-Martinez (research programmer)
- Andreea Tutos (Masters student)
- Patrick Davis-Desmond (Masters student)
Join this Project
There are several ways you can join this project:
- As a PhD student: If you have an interesting topic of research that has to do with question answering and/or summarisation, send us an email and we will get in touch with you.
- As a Masters/Honours student: If you are a Masters or an Honours student in Macquarie University and you are searching for a project, consult the list of Honours projects. Many of these projects can be adapted to Masters projects.
- As an undergraduate student: If you are a student enrolled in Macquarie University you can also work for AnswerFinder and get paid for it. Consult the list of summer projects.
Related Links
- Related Honours Projects
- Related PhD Scholarships
- Other projects at the Centre for Language Technology
Publications
A. Sarker, D. Mollá and C. Paris. An Approach for Automatic Multi-label Classification of
Medical Sentences (2013). Proceedings of the
Fourth International Workshop on Health Document Text Mining and
Information Analysis (LOUHI 2013), Sydney, Australia.
D. Mollá. Experiments with Clustering-based
Features for Sentence Classification in Medical Publications:
Macquarie Test's participation in the ALTA 2012 shared task.
. Proceedings of the 2012 Australasian Language
Technology Workshop
(ALTA
2012), Dunedin, New Zealand.
I. Amini, D. Martinez and D. Mollá. Overview of the
ALTA 2012 Shared Task (2012). Proceedings of the 2012
Australasian Language Technology Workshop
(ALTA
2012), Dunedin, New Zealand.
A. Sarker, D. Mollá and C. Paris. Towards Two-step Multi-document Summarisation for Evidence Based
Medicine: A Quantitative Analysis (2012). Proceedings of
the 2012 Australasian Language Technology Workshop (ALTA 2012),
Dunedin, New Zealand.
D. Martinez, A. MacKinlay, D. Mollá, L. Cavedon and
K. Verspoor. Simple similarity-based question answering
strategies for biomedical text (2012). QA4MRE Workshop
at Conference and Labs of the Evaluation Forum, CLEF
2012. September 17-20, 2012.
D. Mollá
and M.E. Santiago-Martínez. Creation of a Corpus for
Evidence Based Medicine Summarisation
(2012). Australasian Medical
Journal, 5(9).
A. Sarker,
D. Mollá and C. Paris. Extractive Summarisation of
Medical Documents using Domain Knowledge and Corpus Statistics
(2012). Australasian Medical Journal.
A. Sarker,
D. Mollá and C. Paris. Extractive Evidence Based
Medicine Summarisation Based on Sentence-Specific Statistics
(2012). Proceedings of the 25th IEEE International
Symposium on Computer-based Medical Systems (CBMS2012),
Rome, Italy. [slides]
P. Davis-Desmond and Diego Mollá. Detection of
Evidence in Clinical Research Papers
(2012). Australasian Workshop On Health Informatics
and Knowledge Management
(HIKM
2012), Melbourne, Australia. [slides]
- D. Mollá and María Elena Santiago-Martínez. Creation of a Corpus for Evidence Medicine Summarisation (2011). Proceedings of the First Australian Workshop on Artificial Intelligence in Health (AIH 2011), Perth, Australia. [poster]
- A. Sarker, D. Mollá and Cécile Paris. Extractive Summarisation of Medical Documents using Domain Knowledge and Corpus Statistics (2011). Proceedings of the First Australian Workshop on Artificial Intelligence in Health (AIH 2011), Perth, Australia.
D. Mollá and A. Sarker. Automatic Grading of
Evidence: The 2011 ALTA Shared Task (2011). Proceedings of
the 2011 Australasian Language Technology Workshop
(ALTA 2011),
Canberra, Australia.
A. Sarker, D. Mollá and Cécile Paris. Outcome Polarity Identification of Medical Papers (2011). Proceedings of
the 2011 Australasian Language Technology Workshop
(ALTA 2011),
Canberra, Australia.
D. Mollá and María Elena
Santiago-Martínez. Development of a Corpus for
Evidence Medicine Summarisation (2011). Proceedings of
the 2011 Australasian Language Technology Workshop
(ALTA 2011),
Canberra, Australia. [slides]
A. Sarker, D. Mollá and Cécile
Paris. Towards Automatic Grading of Evidence
(2011). Proceedings of the Third International Workshop on
Health Document Text Mining and Information Analysis (LOUHI 2011),
pp51-58. Bled, Slovenia.
A. Sarker and D. Mollá. A Rule-based Approach for
Automatic Identification of Publication Types of Medical Papers (2010).
Proceedings ADCS
2010, 5 pages. Melbourne.
D. Mollá. A Corpus for Evidence Based Medicine Summarisation (2010).
Proceedings ALTA
2010, pp.76-80. Melbourne. [slides>]
A. Tutos and D. Mollá. A Study on the Use of Search Engines for Question Answering in Biomedicine (2010).
Australasian Workshop On Health Informatics and Knowledge Management
(HIKM), 8
pages. Brisbane. [slides]
Other Presentations
Text Summarisation for Evidence Based Medicine, presentation at
the Indo-Australia Workshop on Optimization Techniques for Human
Language Technology, India Institute of Technology Patna, December
16 2012.
Automated Summarisation for Evidence Based Medicine, HAIL seminar
22 March 2012.
Funding
This research is partly funded by a Macquarie University Research Development Grant and by CSIRO.

Parts of this work are licensed under a
GNU General
Public License GPLv3.
Parts of this work are licensed under an
Apache License, Version 2.0.


