Developing ethical and transparent artificial intelligence algorithms to support decision making in healthcare based on brain research and personal care events of patients

Abstract

We propose a new research methodology that develops ethical and transparent artificial intelligence algorithms to support decision making in healthcare. This development relies on a diverse statistical and data analysis methodology based on real-life data gathered in brain research and care events of different patient groups. The proposed new research methodology is created, developed and carried out in a broad international multidisciplinary research collaboration with various patient and disabled people's groups, healthcare professionals, educational institutions, and laboratory measurements of experimental brain research conducted at a biomedical research institute. The proposed new research methodology is motivated by the previous research that has given successful classification results with various bio-inspired artificial intelligence algorithms, based on unsupervised learning (such as various clustering algorithms) and supervised learning (such as artificial neural network algorithms) that are implemented following the structural and functional principles of real-life living biological tissues.