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Outputs (18)

Multi-stage classification of Gyrodactylus species using machine learning and feature selection techniques (2011)
Presentation / Conference Contribution
Ali, R., Hussain, A., Bron, J. E., & Shinn, A. P. (2011, November). Multi-stage classification of Gyrodactylus species using machine learning and feature selection techniques. Presented at 2011 11th International Conference on Intelligent Systems Design and Applications, Cordoba, Spain

This study explores the use of multi-stage machine learning based classifiers and feature selection techniques in the classification and identification of fish parasites. Accurate identification of pathogens is a key to their control and as a proof o... Read More about Multi-stage classification of Gyrodactylus species using machine learning and feature selection techniques.

Switching between different ways to think: Multiple approaches to affective common sense reasoning (2011)
Presentation / Conference Contribution
Cambria, E., Mazzocco, T., Hussain, A., & Durrani, T. (2010, September). Switching between different ways to think: Multiple approaches to affective common sense reasoning. Presented at COST 2102 International Conference, Budapest, Hungary

Emotions are different Ways to Think that our mind triggers to deal with different situations we face in our lives. Our ability to reason and make decisions, in fact, is strictly dependent on both our common sense knowledge about the world and our in... Read More about Switching between different ways to think: Multiple approaches to affective common sense reasoning.

Sentic medoids: Organizing affective common sense knowledge in a multi-dimensional vector space (2011)
Presentation / Conference Contribution
Cambria, E., Mazzocco, T., Hussain, A., & Eckl, C. (2011, May). Sentic medoids: Organizing affective common sense knowledge in a multi-dimensional vector space. Presented at ISNN 2011: 8th International Symposium on Neural Networks, Guilin, China

Existing approaches to opinion mining and sentiment analysis mainly rely on parts of text in which opinions and sentiments are explicitly expressed such as polarity terms and affect words. However, opinions and sentiments are often conveyed implicitl... Read More about Sentic medoids: Organizing affective common sense knowledge in a multi-dimensional vector space.

Sentic avatar: Multimodal affective conversational agent with common sense (2011)
Presentation / Conference Contribution
Cambria, E., Hupont, I., Hussain, A., Cerezo, E., & Baldassarri, S. (2010, March). Sentic avatar: Multimodal affective conversational agent with common sense. Presented at Third COST 2102 International Training School, Caserta, Italy

The capability of perceiving and expressing emotions through different modalities is a key issue for the enhancement of human-computer interaction. In this paper we present a novel architecture for the development of intelligent multimodal affective... Read More about Sentic avatar: Multimodal affective conversational agent with common sense.

Isanette: A common and common sense knowledge base for opinion mining (2011)
Presentation / Conference Contribution
Cambria, E., Song, Y., Wang, H., & Hussain, A. (2011). Isanette: A common and common sense knowledge base for opinion mining. In 2011 IEEE 11th International Conference on Data Mining Workshops (315-322). https://doi.org/10.1109/ICDMW.2011.106

The ability to understand natural language text is far from being emulated in machines. One of the main hurdles to overcome is that computers lack both the common and the common sense knowledge humans normally acquire during the formative years of th... Read More about Isanette: A common and common sense knowledge base for opinion mining.

SimConnector: An approach to testing disaster-alerting systems using agent based simulation models (2011)
Presentation / Conference Contribution
Niazi, M., Siddique, Q., Hussain, A., & Fortino, G. (2011, September). SimConnector: An approach to testing disaster-alerting systems using agent based simulation models. Presented at 2011 Federated Conference on Computer Science and Information Systems (FedCSIS), Szczecin, Poland

The design, development and testing of intelligent disaster detection and alerting systems pose a set of non-trivial problems. Not only are such systems difficult to design as they need to accurately predict real-world outcomes using a distributed se... Read More about SimConnector: An approach to testing disaster-alerting systems using agent based simulation models.

Ontology-driven cardiovascular decision support system (2011)
Presentation / Conference Contribution
Farooq, K., Hussain, A., Leslie, S., Eckl, C., & Slack, W. (2011, May). Ontology-driven cardiovascular decision support system. Presented at 2011 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops, Dublin, Ireland

We discuss work-in-progress and propose an ontology driven framework for the development of a clinical expert system for chest pain risk assessment. The framework has the following key components: adaptive questionnaire, patient medical history, risk... Read More about Ontology-driven cardiovascular decision support system.

A side-effects mapping model in patients with lung, colorectal and breast cancer receiving chemotherapy (2011)
Presentation / Conference Contribution
Mazzocco, T., & Hussain, A. (2011, June). A side-effects mapping model in patients with lung, colorectal and breast cancer receiving chemotherapy. Presented at 2011 IEEE 13th International Conference on e-Health Networking, Applications and Services, Columbia, MO, USA

Cancer treatments are now more effective than ever and, as a consequence, cancer is becoming a chronic disease. Chemotherapy is a frequently used treatment in people with cancer and it can cause a number of side-effects which if not properly managed... Read More about A side-effects mapping model in patients with lung, colorectal and breast cancer receiving chemotherapy.

Novel logistic regression models to aid the diagnosis of dementia (2011)
Journal Article
Mazzocco, T., & Hussain, A. (2012). Novel logistic regression models to aid the diagnosis of dementia. Expert Systems with Applications, 39(3), 3356-3361. https://doi.org/10.1016/j.eswa.2011.09.023

Clinicians often experience difficulties in the diagnosis of dementia due to the intrinsic complexity of the process and lack of comprehensive diagnostic tools. Different models have been proposed to provide medical decision support in dementia diagn... Read More about Novel logistic regression models to aid the diagnosis of dementia.