All Outputs (11)

Genetic Algorithms as a Feature Selection Tool in Heart Failure Disease (2020)
Presentation / Conference Contribution
Alabed, A., Kambhampati, C., & Gordon, N. Genetic Algorithms as a Feature Selection Tool in Heart Failure Disease. Presented at Computing 2020, London

A great wealth of information is hidden in clinical datasets, which could be analyzed to support decision-making processes or to better diagnose patients. Feature selection is one of the data pre-processing that selects a set of input features by rem... Read More about Genetic Algorithms as a Feature Selection Tool in Heart Failure Disease.

An evaluation framework for mobile health education software (2015)
Presentation / Conference Contribution
Aljaber, T., Gordon, N., Kambhampati, C., & Brayshaw, M. (2015, July). An evaluation framework for mobile health education software. Presented at 2015 Science and Information Conference (SAI), London

© 2015 IEEE. Mobile applications in general, and mobile applications for health education in particular, are commonly used to support patients, health professionals and other stakeholders. A critical evaluation framework is needed to ensure the usabi... Read More about An evaluation framework for mobile health education software.

A comparative study of missing value imputation with multiclass classification for clinical heart failure data (2012)
Presentation / Conference Contribution
Zhang, Y., Kambhampati, C., Davis, D. N., Goode, K., & Cleland, J. G. F. A comparative study of missing value imputation with multiclass classification for clinical heart failure data. Presented at 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery

Clinical data often contains missing values. Imputation is one of the best known schemes to overcome the drawbacks associated with missing values in data mining tasks. In this work, we compared several imputation methods and analyzed their performanc... Read More about A comparative study of missing value imputation with multiclass classification for clinical heart failure data.

Chaotic oscillations in a Hodgkin-Huxley neuron - Quantifying similarity estimation of neural responses (2010)
Presentation / Conference Contribution
Sarangdhar, M., & Kambhampati, C. (2010, June). Chaotic oscillations in a Hodgkin-Huxley neuron - Quantifying similarity estimation of neural responses. Presented at WCE 2010 - World Congress on Engineering 2010, London; United Kingdom

Dysphonia measures in parkinson's disease and their use in prediction of its progression (2010)
Presentation / Conference Contribution
Kambhampati, C., Sarangdhar, M., & Poolsawad, N. (2010, October). Dysphonia measures in parkinson's disease and their use in prediction of its progression. Presented at International Conference on Knowledge Engineering and Ontology Development, Valencia, Spain

Parkinson's Disease (PD) is a neurodegenerative disorder that impairs the motor skills, speech and general muscle coordination. The progression of PD is assessed using a clinically defined rating scale known as Unified Parkinson's Disease Rating Scal... Read More about Dysphonia measures in parkinson's disease and their use in prediction of its progression.

Stimulus reconstruction from a Hodgkin-Huxley neural response: A numerical solution (2010)
Presentation / Conference Contribution
Sarangdhar, M., & Kambhampati, C. (2010, June). Stimulus reconstruction from a Hodgkin-Huxley neural response: A numerical solution. Presented at World Congress on Engineering 2010

Neural responses are the fundamental expressions of any neural activity. Information carried by a neural response is determined by the nature of a neural activity. In majority of cases the underlying stimulus that triggers it remains largely... Read More about Stimulus reconstruction from a Hodgkin-Huxley neural response: A numerical solution.

Spiking neurons: Is coincidence-factor enough for comparing responses with fluctuating membrane voltage? (2008)
Presentation / Conference Contribution
Sarangdhar, M., & Kambhampati, C. Spiking neurons: Is coincidence-factor enough for comparing responses with fluctuating membrane voltage?

Similarity between two spike trains is generally estimated using a ‘coincidence factor’. This factor relies on counting coincidences of firing-times for spikes in a given time window. However, in cases where there are significant fluctuations in memb... Read More about Spiking neurons: Is coincidence-factor enough for comparing responses with fluctuating membrane voltage?.

The current opinion on the use of robots for landmine detection (2003)
Presentation / Conference Contribution
Rajasekharan, S., & Kambhampati, C. The current opinion on the use of robots for landmine detection. Presented at 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422), Taipei, Taiwan, Taiwan

Anti-Personal landmines are a significant barrier to economic and social development in a number of countries. Several sensors have been developed but each one will probably have to find, if it exists, a specific area of applicability, determined by... Read More about The current opinion on the use of robots for landmine detection.

Trained Hopfield neural networks need not be black-boxes (1999)
Presentation / Conference Contribution
Craddock, R., & Kambhampati, C. (1999, June). Trained Hopfield neural networks need not be black-boxes. Presented at Proceedings of the 1999 American Control Conference, San Diego, CA, USA

Stable linearization using multilayer neural networks (1996)
Presentation / Conference Contribution
Delgado, A., Kambhampati, C., & Warwick, K. (1996, September). Stable linearization using multilayer neural networks. Presented at UKACC International Conference on Control. Control '96, Exeter, UK

The main limitation of linearization theory that prevents its application in practical problems is the need for an exact knowledge of the plant. This requirement is eliminated and it is shown that a multilayer network can synthesise the state feedbac... Read More about Stable linearization using multilayer neural networks.

The relative order of a class of recurrent networks (1994)
Presentation / Conference Contribution
Manchanda, S., Kambhampati, C., Tham, M., & Green, G. (1994, March). The relative order of a class of recurrent networks. Presented at International Conference on Control '94, Coventry, UK

Three types of recurrent network configurations have been proposed since they enable adequate description of temporal behaviour. The concept of relative order has been introduced so as to provide a framework for analysing such network configurations.... Read More about The relative order of a class of recurrent networks.