All Outputs (3)

Dynamic risk stratification using Markov chain modelling in patients with chronic heart failure (2022)
Journal Article
Kazmi, S., Kambhampati, C., Cleland, J., Cuthbert, J., Kazmi, K. S., Pellicori, P., …Clark, A. L. (2022). Dynamic risk stratification using Markov chain modelling in patients with chronic heart failure. ESC Heart Failure, https://doi.org/10.1002/ehf2.14028

Aims: Risk changes with the progression of disease and the impact of treatment. We developed a dynamic risk stratification Markov chain model using artificial intelligence in patients with chronic heart failure (CHF). Methods and results: We describe... Read More about Dynamic risk stratification using Markov chain modelling in patients with chronic heart failure.

Locally fitting hyperplanes to high-dimensional data (2022)
Journal Article
Hou, M., & Kambhampati, C. (2022). Locally fitting hyperplanes to high-dimensional data. Neural Computing and Applications, 34(11), 8885-8896. https://doi.org/10.1007/s00521-022-06909-y

Problems such as data compression, pattern recognition and artificial intelligence often deal with a large data sample as observations of an unknown object. An effective method is proposed to fit hyperplanes to data points in each hypercubic subregio... Read More about Locally fitting hyperplanes to high-dimensional data.

Addressing Optimisation Challenges for Datasets with Many Variables, Using Genetic Algorithms to Implement Feature Selection (2022)
Journal Article
Gordon, N., Kambhampati, C., & Alabad, A. (2022). Addressing Optimisation Challenges for Datasets with Many Variables, Using Genetic Algorithms to Implement Feature Selection. AI, Computer Science and Robotics Technology, 1, 1-21. https://doi.org/10.5772/acrt.01

This article provides an optimisation method using a Genetic Algorithm approach to apply feature selection techniques for large data sets to improve accuracy. This is achieved through improved classification, a reduced number of features, and further... Read More about Addressing Optimisation Challenges for Datasets with Many Variables, Using Genetic Algorithms to Implement Feature Selection.