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Workshop Details
BioDM: Workshop on Biological Data Mining and its Applications in Healthcare
Organized by Xiao-Li Li, See-Kiong Ng and Jason T. L. Wang
08:30 - 17:40
Room: Permeke
http://www1.i2r.a-star.edu.sg/~xlli/BioDM.html
In this BioDM workshop, we address the challenging issues in various biological and healthcare data analysis. The workshop, held in Brussels Belgium on December 10 2012, has garnered great response from the researchers and received a total of 29 paper submissions (16 workshop submissions; 13 transferred main conference submissions), out of which 14 (48.3%) were selected for presentation at the workshop. We would like to thank all the authors who have submitted their papers on many exciting and important research topics. We also thank the presenters of the accepted papers. Last but not least, we thank all the workshop participants for attending this third workshop in Brussels Belgium. It is our hope that the workshop will provide a lasting platform for disseminating the latest research results and practice of the data mining approaches in biology and healthcare.
| 08:30 - 08:50 | Welcoming and Introduction Xiao-Li Li |
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08:30 - 08:50 | Welcoming and Introduction Xiao-Li Li |
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08:30 - 08:50 | Welcoming and Introduction | event_type == 4) {?>Welcoming and Introduction | event_type == 5) {?>08:30 - 08:50 | Welcoming and Introduction Xiao-Li Li |
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| 08:50 - 09:40 | Invited Talk: Modeling complex diseases using discriminative network fragments Ambuj Singh, University of California at Santa Barbara |
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08:50 - 09:40 | Invited Talk: Modeling complex diseases using discriminative network fragments Ambuj Singh, University of California at Santa Barbara |
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08:50 - 09:40 | Invited Talk: Modeling complex diseases using discriminative network fragments | event_type == 4) {?>Invited Talk: Modeling complex diseases using discriminative network fragments | event_type == 5) {?>08:50 - 09:40 | Invited Talk: Modeling complex diseases using discriminative network fragments Ambuj Singh, University of California at Santa Barbara |
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| 09:40 - 12:30 | Morning Session: Classification, Decision making, Visualization |
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09:40 - 12:30 | Morning Session: Classification, Decision making, Visualization |
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09:40 - 12:30 | Morning Session: Classification, Decision making, Visualization | event_type == 4) {?>Morning Session: Classification, Decision making, Visualization | event_type == 5) {?>09:40 - 12:30 | Morning Session: Classification, Decision making, Visualization |
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| 09:40 - 10:00 | Adapting Surgical Models to Individual Hospitals using Transfer Learning Gyemin Lee, Ilan Rubinfeld, and Zeeshan Syed |
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09:40 - 10:00 | Adapting Surgical Models to Individual Hospitals using Transfer Learning Gyemin Lee, Ilan Rubinfeld, and Zeeshan Syed |
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09:40 - 10:00 | Adapting Surgical Models to Individual Hospitals using Transfer Learning | event_type == 4) {?>Adapting Surgical Models to Individual Hospitals using Transfer Learning | event_type == 5) {?>09:40 - 10:00 | Adapting Surgical Models to Individual Hospitals using Transfer Learning Gyemin Lee, Ilan Rubinfeld, and Zeeshan Syed |
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| 10:00 - 10:30 | Coffee Break |
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10:00 - 10:30 | Coffee Break |
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10:00 - 10:30 | Coffee Break | event_type == 4) {?>Coffee Break | event_type == 5) {?>10:00 - 10:30 | Coffee Break |
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| 10:30 - 10:50 | Mining medical data to develop clinical decision making tools in hemodialysis - Prediction of cardiovascular events in incident hemodialysis patients: Jasmine Ion Titapiccolo, Manuela Ferrario, Maria Gabriella Signorini, Sergio Cerutti, Carlo Barbieri, Flavio Mari, and Emanuele Gatti |
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10:30 - 10:50 | Mining medical data to develop clinical decision making tools in hemodialysis - Prediction of cardiovascular events in incident hemodialysis patients: Jasmine Ion Titapiccolo, Manuela Ferrario, Maria Gabriella Signorini, Sergio Cerutti, Carlo Barbieri, Flavio Mari, and Emanuele Gatti |
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10:30 - 10:50 | Mining medical data to develop clinical decision making tools in hemodialysis - Prediction of cardiovascular events in incident hemodialysis patients: | event_type == 4) {?>Mining medical data to develop clinical decision making tools in hemodialysis - Prediction of cardiovascular events in incident hemodialysis patients: | event_type == 5) {?>10:30 - 10:50 | Mining medical data to develop clinical decision making tools in hemodialysis - Prediction of cardiovascular events in incident hemodialysis patients: Jasmine Ion Titapiccolo, Manuela Ferrario, Maria Gabriella Signorini, Sergio Cerutti, Carlo Barbieri, Flavio Mari, and Emanuele Gatti |
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| 10:50 - 11:10 | Cerebral Palsy EEG signals Classification: Facial Expressions and Thoughts for Driving an Intelligent Wheelchair Brigida Monica Faria |
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10:50 - 11:10 | Cerebral Palsy EEG signals Classification: Facial Expressions and Thoughts for Driving an Intelligent Wheelchair Brigida Monica Faria |
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10:50 - 11:10 | Cerebral Palsy EEG signals Classification: Facial Expressions and Thoughts for Driving an Intelligent Wheelchair | event_type == 4) {?>Cerebral Palsy EEG signals Classification: Facial Expressions and Thoughts for Driving an Intelligent Wheelchair | event_type == 5) {?>10:50 - 11:10 | Cerebral Palsy EEG signals Classification: Facial Expressions and Thoughts for Driving an Intelligent Wheelchair Brigida Monica Faria |
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| 11:10 - 11:30 | Diagnosis of Coronary Artery Disease Using Cost-Sensitive Algorithms Roohallah Alizadehsani, Mohammad Javad Hosseini, Zahra Alizadeh Sani, Asma Ghandeharioun, and Reihane Boghrati |
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11:10 - 11:30 | Diagnosis of Coronary Artery Disease Using Cost-Sensitive Algorithms Roohallah Alizadehsani, Mohammad Javad Hosseini, Zahra Alizadeh Sani, Asma Ghandeharioun, and Reihane Boghrati |
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11:10 - 11:30 | Diagnosis of Coronary Artery Disease Using Cost-Sensitive Algorithms | event_type == 4) {?>Diagnosis of Coronary Artery Disease Using Cost-Sensitive Algorithms | event_type == 5) {?>11:10 - 11:30 | Diagnosis of Coronary Artery Disease Using Cost-Sensitive Algorithms Roohallah Alizadehsani, Mohammad Javad Hosseini, Zahra Alizadeh Sani, Asma Ghandeharioun, and Reihane Boghrati |
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| 11:30 - 11:50 | Evidence Theory-based Approach for Epileptic Seizure Detection Abduljalil Mohamed, Khaled Shaban, and Amr Mohamed |
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11:30 - 11:50 | Evidence Theory-based Approach for Epileptic Seizure Detection Abduljalil Mohamed, Khaled Shaban, and Amr Mohamed |
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11:30 - 11:50 | Evidence Theory-based Approach for Epileptic Seizure Detection | event_type == 4) {?>Evidence Theory-based Approach for Epileptic Seizure Detection | event_type == 5) {?>11:30 - 11:50 | Evidence Theory-based Approach for Epileptic Seizure Detection Abduljalil Mohamed, Khaled Shaban, and Amr Mohamed |
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| 11:50 - 12:10 | Predicting Hospital Length of Stay (PHLOS) : A Multi-Tiered Data Mining approach Ali Azari, Vandana P. Janeja, and Alex Mohseni |
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11:50 - 12:10 | Predicting Hospital Length of Stay (PHLOS) : A Multi-Tiered Data Mining approach Ali Azari, Vandana P. Janeja, and Alex Mohseni |
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11:50 - 12:10 | Predicting Hospital Length of Stay (PHLOS) : A Multi-Tiered Data Mining approach | event_type == 4) {?>Predicting Hospital Length of Stay (PHLOS) : A Multi-Tiered Data Mining approach | event_type == 5) {?>11:50 - 12:10 | Predicting Hospital Length of Stay (PHLOS) : A Multi-Tiered Data Mining approach Ali Azari, Vandana P. Janeja, and Alex Mohseni |
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| 12:10 - 12:30 | Using perspective wall to visualize medical data in the Intensive Care Unit Hela LTIFI, Mounir Ben Ayed, Ghada Trabelsi, and M. Adel ALIMI |
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12:10 - 12:30 | Using perspective wall to visualize medical data in the Intensive Care Unit Hela LTIFI, Mounir Ben Ayed, Ghada Trabelsi, and M. Adel ALIMI |
event_type == 3) {?>
12:10 - 12:30 | Using perspective wall to visualize medical data in the Intensive Care Unit | event_type == 4) {?>Using perspective wall to visualize medical data in the Intensive Care Unit | event_type == 5) {?>12:10 - 12:30 | Using perspective wall to visualize medical data in the Intensive Care Unit Hela LTIFI, Mounir Ben Ayed, Ghada Trabelsi, and M. Adel ALIMI |
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| 12:30 - 14:00 | Lunch Break |
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12:30 - 14:00 | Lunch Break |
event_type == 3) {?>
12:30 - 14:00 | Lunch Break | event_type == 4) {?>Lunch Break | event_type == 5) {?>12:30 - 14:00 | Lunch Break |
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| 14:00 - 14:50 | Invited Talk: Perspectives of feature selection in bioinformatics: from relevance to causal inference Bontempi Gianluca, Université Libre de Bruxelles |
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14:00 - 14:50 | Invited Talk: Perspectives of feature selection in bioinformatics: from relevance to causal inference Bontempi Gianluca, Université Libre de Bruxelles |
event_type == 3) {?>
14:00 - 14:50 | Invited Talk: Perspectives of feature selection in bioinformatics: from relevance to causal inference | event_type == 4) {?>Invited Talk: Perspectives of feature selection in bioinformatics: from relevance to causal inference | event_type == 5) {?>14:00 - 14:50 | Invited Talk: Perspectives of feature selection in bioinformatics: from relevance to causal inference Bontempi Gianluca, Université Libre de Bruxelles |
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| 14:50 - 17:40 | Afternoon Session: Feature selection, Clustering, Data fusion, Retrieval, Graph mining |
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14:50 - 17:40 | Afternoon Session: Feature selection, Clustering, Data fusion, Retrieval, Graph mining |
event_type == 3) {?>
14:50 - 17:40 | Afternoon Session: Feature selection, Clustering, Data fusion, Retrieval, Graph mining | event_type == 4) {?>Afternoon Session: Feature selection, Clustering, Data fusion, Retrieval, Graph mining | event_type == 5) {?>14:50 - 17:40 | Afternoon Session: Feature selection, Clustering, Data fusion, Retrieval, Graph mining |
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| 14:50 - 15:10 | Coupled Matrix Factorization with Sparse Factors to Identify Potential Biomarkers in Metabolomics Evrim Acar, Gozde Gurdeniz, Morten A. Rasmussen, Daniela Rago, Lars O. Dragsted, and Rasmus Bro |
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14:50 - 15:10 | Coupled Matrix Factorization with Sparse Factors to Identify Potential Biomarkers in Metabolomics Evrim Acar, Gozde Gurdeniz, Morten A. Rasmussen, Daniela Rago, Lars O. Dragsted, and Rasmus Bro |
event_type == 3) {?>
14:50 - 15:10 | Coupled Matrix Factorization with Sparse Factors to Identify Potential Biomarkers in Metabolomics | event_type == 4) {?>Coupled Matrix Factorization with Sparse Factors to Identify Potential Biomarkers in Metabolomics | event_type == 5) {?>14:50 - 15:10 | Coupled Matrix Factorization with Sparse Factors to Identify Potential Biomarkers in Metabolomics Evrim Acar, Gozde Gurdeniz, Morten A. Rasmussen, Daniela Rago, Lars O. Dragsted, and Rasmus Bro |
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| 15:10 - 15:30 | Clustering Tandem Repeats Via Trinucleotides Yupu Liang, Dina Sokol, and Sarah Zelikovitz |
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15:10 - 15:30 | Clustering Tandem Repeats Via Trinucleotides Yupu Liang, Dina Sokol, and Sarah Zelikovitz |
event_type == 3) {?>
15:10 - 15:30 | Clustering Tandem Repeats Via Trinucleotides | event_type == 4) {?>Clustering Tandem Repeats Via Trinucleotides | event_type == 5) {?>15:10 - 15:30 | Clustering Tandem Repeats Via Trinucleotides Yupu Liang, Dina Sokol, and Sarah Zelikovitz |
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| 15:30 - 16:00 | Coffee Break |
event_type == 2) {?>
15:30 - 16:00 | Coffee Break |
event_type == 3) {?>
15:30 - 16:00 | Coffee Break | event_type == 4) {?>Coffee Break | event_type == 5) {?>15:30 - 16:00 | Coffee Break |
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| 16:00 - 16:20 | Evaluation of Feature Ranking Ensembles for High-Dimensional Biomedical Data: A Case Study Ludmila Kuncheva, Christopher Smith, Yasir Syed, Christopher Phillips, and Keir Lewis |
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16:00 - 16:20 | Evaluation of Feature Ranking Ensembles for High-Dimensional Biomedical Data: A Case Study Ludmila Kuncheva, Christopher Smith, Yasir Syed, Christopher Phillips, and Keir Lewis |
event_type == 3) {?>
16:00 - 16:20 | Evaluation of Feature Ranking Ensembles for High-Dimensional Biomedical Data: A Case Study | event_type == 4) {?>Evaluation of Feature Ranking Ensembles for High-Dimensional Biomedical Data: A Case Study | event_type == 5) {?>16:00 - 16:20 | Evaluation of Feature Ranking Ensembles for High-Dimensional Biomedical Data: A Case Study Ludmila Kuncheva, Christopher Smith, Yasir Syed, Christopher Phillips, and Keir Lewis |
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| 16:20 - 16:40 | Improved Feature Selection by Incorporating Gene Similarity into the LASSO Christopher Gillies, Xiaoli Gao, Nilesh Patel, Mohammad Siadat, and George Wilson |
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16:20 - 16:40 | Improved Feature Selection by Incorporating Gene Similarity into the LASSO Christopher Gillies, Xiaoli Gao, Nilesh Patel, Mohammad Siadat, and George Wilson |
event_type == 3) {?>
16:20 - 16:40 | Improved Feature Selection by Incorporating Gene Similarity into the LASSO | event_type == 4) {?>Improved Feature Selection by Incorporating Gene Similarity into the LASSO | event_type == 5) {?>16:20 - 16:40 | Improved Feature Selection by Incorporating Gene Similarity into the LASSO Christopher Gillies, Xiaoli Gao, Nilesh Patel, Mohammad Siadat, and George Wilson |
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| 16:40 - 17:00 | Discovering Aberrant Patterns of Human Connectcome in Alzheimerís Disease via Subgraph Mining Junming Shao |
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16:40 - 17:00 | Discovering Aberrant Patterns of Human Connectcome in Alzheimerís Disease via Subgraph Mining Junming Shao |
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16:40 - 17:00 | Discovering Aberrant Patterns of Human Connectcome in Alzheimerís Disease via Subgraph Mining | event_type == 4) {?>Discovering Aberrant Patterns of Human Connectcome in Alzheimerís Disease via Subgraph Mining | event_type == 5) {?>16:40 - 17:00 | Discovering Aberrant Patterns of Human Connectcome in Alzheimerís Disease via Subgraph Mining Junming Shao |
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| 17:00 - 17:20 | Figure Retrieval in Biomedical Literature P Radha Krishna, K Sai Deepak, and Harikrishna G N Rai |
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17:00 - 17:20 | Figure Retrieval in Biomedical Literature P Radha Krishna, K Sai Deepak, and Harikrishna G N Rai |
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17:00 - 17:20 | Figure Retrieval in Biomedical Literature | event_type == 4) {?>Figure Retrieval in Biomedical Literature | event_type == 5) {?>17:00 - 17:20 | Figure Retrieval in Biomedical Literature P Radha Krishna, K Sai Deepak, and Harikrishna G N Rai |
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| 17:20 - 17:40 | Discovering aging-genes by topological features in Drosophila melanogaster protein--protein interaction network Xin Song, Yuan-Chun Zhou, Kai Feng, Yan-Hui Li, and Jian-Hui Li |
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17:20 - 17:40 | Discovering aging-genes by topological features in Drosophila melanogaster protein--protein interaction network Xin Song, Yuan-Chun Zhou, Kai Feng, Yan-Hui Li, and Jian-Hui Li |
event_type == 3) {?>
17:20 - 17:40 | Discovering aging-genes by topological features in Drosophila melanogaster protein--protein interaction network | event_type == 4) {?>Discovering aging-genes by topological features in Drosophila melanogaster protein--protein interaction network | event_type == 5) {?>17:20 - 17:40 | Discovering aging-genes by topological features in Drosophila melanogaster protein--protein interaction network Xin Song, Yuan-Chun Zhou, Kai Feng, Yan-Hui Li, and Jian-Hui Li |
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