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3. Translational Medicine Informatics Services from the Bedside Over QL4POMR

Author

Mohammed, Sabah, Fiaidhi, Jinan, Sawyer, Darien, Sertic, Peter, Barbosa-Povoa, Ana Paula, Editorial Board Member, de Almeida, Adiel Teixeira, Editorial Board Member, Gans, Noah, Editorial Board Member, Gupta, Jatinder N. D., Editorial Board Member, Heim, Gregory R., Editorial Board Member, Hua, Guowei, Editorial Board Member, Kimms, Alf, Editorial Board Member, Li, Xiang, Editorial Board Member, Masri, Hatem, Editorial Board Member, Nickel, Stefan, Editorial Board Member, Qiu, Robin, Editorial Board Member, Shankar, Ravi, Editorial Board Member, Slowiński, Roman, Editorial Board Member, Tang, Christopher S., Editorial Board Member, Wu, Yuzhe, Editorial Board Member, Zhu, Joe, Editorial Board Member, Zopounidis, Constantin, Editorial Board Member, Shang, Xiaopu, editor, Fu, Xiaowen, editor, Ma, Yixuan, editor, Gong, Daqing, editor, and Zhang, Juliang, editor

Published
2023
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6. Thick Data Analytics for Small Training Samples Using Siamese Neural Network and Image Augmentation

Author

Fiaidhi, Jinan, Sawyer, Darien, Mohammed, Sabah, Barbosa-Povoa, Ana Paula, Editorial Board Member, de Almeida, Adiel Teixeira, Editorial Board Member, Gans, Noah, Editorial Board Member, Gupta, Jatinder N. D., Editorial Board Member, Heim, Gregory R., Editorial Board Member, Hua, Guowei, Editorial Board Member, Kimms, Alf, Editorial Board Member, Li, Xiang, Editorial Board Member, Masri, Hatem, Editorial Board Member, Nickel, Stefan, Editorial Board Member, Qiu, Robin, Editorial Board Member, Shankar, Ravi, Editorial Board Member, Slowiński, Roman, Editorial Board Member, Tang, Christopher S., Editorial Board Member, Wu, Yuzhe, Editorial Board Member, Zhu, Joe, Editorial Board Member, Zopounidis, Constantin, Editorial Board Member, Shi, Xianliang, editor, Bohács, Gábor, editor, Ma, Yixuan, editor, Gong, Daqing, editor, and Shang, Xiaopu, editor

Published
2022
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7. QL4POMR Interface as a Graph-Based Clinical Diagnosis Web Service

Author

Mohammed, Sabah, Fiaidhi, Jinan, Sawyer, Darien, Barbosa-Povoa, Ana Paula, Editorial Board Member, de Almeida, Adiel Teixeira, Editorial Board Member, Gans, Noah, Editorial Board Member, Gupta, Jatinder N. D., Editorial Board Member, Heim, Gregory R., Editorial Board Member, Hua, Guowei, Editorial Board Member, Kimms, Alf, Editorial Board Member, Li, Xiang, Editorial Board Member, Masri, Hatem, Editorial Board Member, Nickel, Stefan, Editorial Board Member, Qiu, Robin, Editorial Board Member, Shankar, Ravi, Editorial Board Member, Slowiński, Roman, Editorial Board Member, Tang, Christopher S., Editorial Board Member, Wu, Yuzhe, Editorial Board Member, Zhu, Joe, Editorial Board Member, Zopounidis, Constantin, Editorial Board Member, Shi, Xianliang, editor, Bohács, Gábor, editor, Ma, Yixuan, editor, Gong, Daqing, editor, and Shang, Xiaopu, editor

Published
2022
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30. Developing a Secure Distributed OSGi Cloud Computing Infrastructure for Sharing Health Records

Author

Mohammed, Sabah, Servos, Daniel, Fiaidhi, Jinan, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Kamel, Mohamed, editor, Karray, Fakhri, editor, Gueaieb, Wail, editor, and Khamis, Alaa, editor

Published
2011
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36. The Roadmap for Sharing Electronic Health Records: The Emerging Ubiquity and Cloud Computing Trends

Author

Mohammed, Sabah, Fiaidhi, Jinan, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Kim, Tai-hoon, editor, Lee, Young-hoon, editor, Kang, Byeong-Ho, editor, and Ślęzak, Dominik, editor

Published
2010
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37. Collaborative Virtual Learning Model for Web Intelligence

Author

Fiaidhi, Jinan A. W., Mohammed, Sabah M. A., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Dough, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Shen, Wei-ming, editor, Chao, Kuo-Ming, editor, Lin, Zongkai, editor, Barthès, Jean-Paul A., editor, and James, Anne, editor

Published
2006
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39. Empowering multi-class medical data classification by Group-of-Single-Class-predictors and transfer optimization:Cases of structured dataset by machine learning and radiological images by deep learning

Author

Li, Tengyue, Fong, Simon, Mohammed, Sabah, Fiaidhi, Jinan, Guan, Steven, and Chang, Victor

Abstract

In the medical domain, data are often collected over time, evolving from simple to refined categories. The data and the underlying structures of the medical data as to how they have grown to today's complexity can be decomposed into crude forms when data collection starts. For instance, the cancer dataset is labeled either benign or malignant at its simplest or perhaps the earliest form. As medical knowledge advances and/or more data become available, the dataset progresses from binary class to multi-class, having more labels of sub-categories of the disease added. In machine learning, inducing a multi-class model requires more computational power. Model optimization is enforced over the multi-class models for the highest possible accuracy, which of course, is necessary for life-and-death decision making. This model optimization task consumes an extremely long model training time. In this paper, a novel strategy called Group-of-Single-Class prediction (GOSC) coupled with majority voting and model transfer is proposed for achieving maximum accuracy by using only a fraction of the model training time. The main advantage is the ability to achieve an optimized multi-class classification model that has the highest possible accuracy near to the absolute maximum, while the training time could be saved by up to 70%. Experiments on machine learning over liver dataset classification and deep learning over COVID19 lung CT images were tested. Preliminary results suggest the feasibility of this new approach.

Published
2022

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