Archive | BioInfoMed’2022 ⬛ Prof. Nikola Kasabov: “Current Challenges and Current Solutions in Biomedical Data Science: Personalisation; Explainability; Multi-modality; Model adaptation”

Abstract

 
The talk presents 4 current challenges in biomedical data science, namely:

1. Personalised modelling for early diagnosis and prognosis of a disease.
2. Explainability and profiling at a personal level for a better treatment.
3. Multiple modality of data, such as genetic, clinical, behaviour, cognitive, static, temporal.
4. Incremental adaptability of the models with new data being made available continuously.

The talk presents also current solutions, such as Evolving Connectionist Systems (ECOS) and brain-inspired spiking neural networks (SNN) developed by the author and his team. The ECOS models, such as EFuNN and DENFIS [1,2] offer efficient solutions to all challenges from 1 to 4 above on vector-based data, while SNN, such as NeuCube [2,3] offer a general solution for integrated vector-based and temporal data, including longitudinal data. The talk describes briefly the two classes of models (ECOS and SNN NeuCube) and how they can be used to address the above 4 challenges.

Experimental results from several projects led by the author are discussed, including:

• Early diagnosis and personalised profiling of cancer.
• Predicting AD from longitudinal MRI and multimodal data.
• Personalised prediction of stroke.
• Predicting response to treatment of drug addicts and patients of Schizophrenia.
• Early diagnosis of Psychosis and Schizophrenia based on genetic and cognitive data.

The above applications have been developed in the development software NeuCom [2] and NeuCube [4], which are available free.

[1] N.Kasabov, Evolving Connectionist Systems, Springer, 2007

[2] NeuCom: https://theneucom.com

[3] N.Kasabov, Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence, Springer, 2019,
https://www.springer.com/gp/book/9783662577134.

[4]  NeuCube: https://kedri.aut.ac.nz/neucube

Curriculum Vitae

Professor Nikola (Nik) K Kasabov (also known as Kassabov) is Life Fellow of IEEE, Fellow of the Royal Society of New Zealand, Fellow of the INNS College of Fellows, DVF of the Royal Academy of Engineering UK. He is the Founding Director of the Knowledge Engineering and Discovery Research Institute (KEDRI), Auckland and Professor at the School of Engineering, Computing and Mathematical Sciences at Auckland University of Technology, New Zealand. He is also George Moore Chair Professor of Data Analytics at the University of Ulster UK, Honorary Professor at the Teesside University UK and the University of Auckland NZ, Visiting Professor at the IICT Bulgarian Academy of Sciences and Peking University in Shenzhen. Kasabov is Past President of the Asia Pacific Neural Network Society (APNNS) and the International Neural Network Society (INNS). He has been a chair and a member of several technical committees of IEEE Computational Intelligence Society and Distinguished Lecturer of IEEE (2012-2014). He is Editor of Springer Handbook of Bio-Neuroinformatics, EIC of Springer Series of Bio-and Neuro-systems and co-EIC of the Springer journal Evolving Systems. He is Associate Editor of several journals, including Neural Networks, IEEE TrNN, Tr CDS, Information Sciences, Applied Soft Computing. Kasabov holds MSc and PhD from TU Sofia, Bulgaria. His main research interests are in the areas of neural networks, intelligent information systems, soft computing, bioinformatics, neuroinformatics. He has published more than 700 publications, highly cited internationally. He has extensive academic experience at various academic and research organisations in Europe and Asia, including: TU Sofia Bulgaria; University of Essex UK; University of Otago, NZ; Shanghai Jiao Tong University and CASIA China, ETH/University of Zurich. He is currently a Visiting Professor at the IICT Bulgarian Academy of Sciences, Peking University in Shenzhen and Dalian University China. Kasabov has received a number of awards, among them: Doctor Honoris Causa from Obuda University; INNS Ada Lovelace Meritorious Service Award; NN journal Best Paper Award for 2016; APNNA ‘Outstanding Achievements Award’; INNS Gabor Award for ‘Outstanding contributions to engineering applications of neural networks’; EU Marie Curie Fellowship; Bayer Science Innovation Award; APNNA Excellent Service Award; RSNZ Science and Technology Medal; 2015 AUT NZ Medal; Medal “Bacho Kiro” of the SU Pavlikeni, Honorary Member of the Bulgarian, the Greek and the Scottish Societies for Computer Science, Honorary Citizen of Pavlikeni – Bulgaria. More information of Prof. Kasabov can be found from: https://academics.aut.ac.nz/nkasabov. Born Svistov Bulgaria. Daughters: Kapka Kassabova, Assia Kassabova. Wife: Diana Kassabova.