Cambridge scientists have developed an artificially-intelligent tool capable of predicting in four cases out of five whether people with early signs of dementia will remain stable or develop Alzheimer's disease.
Jul 13, 2024
Sep 5, 2017 · Abstract:This paper presents the EACare project, an ambitious multi-disciplinary collaboration with the aim to develop an embodied system, ...
Abstract. This paper presents the EACare project, an ambitious multi- disciplinary collaboration with the aim to develop an embodied system,.
This paper presents the EACare project, an ambitious multi-disciplinary collaboration with the aim to develop an embodied system, capable of carrying out ...
Sep 20, 2017 · The system will use methods from Machine Learning and Social Robotics, and be trained with examples of recorded clinician-patient interactions.
This position paper presented the EACare project, where we aim to develop a system with an embodied agent, that can carry out neuropsychological clinical tests ...
Artificial Intelligence for Dementia Research Methods Optimization
pmc.ncbi.nlm.nih.gov › PMC10002770
We present an overview of ML algorithms most frequently used in dementia research and highlight future opportunities for the use of ML in clinical practice.
Aug 26, 2024 · Scientists from Edinburgh and Dundee will use AI and brain scans from the entire Scottish population to build a software tool that they hope ...
Sep 19, 2023 · This paper proposes a machine learning approach to address this issue, utilizing cognitive and neuroimaging features for training predictive models.
Feb 18, 2020 · html. Create Close. Machine Learning and Social Robotics for Detecting Early Signs of Dementia. Jonell, Patrik. KTH, School of Computer Science ...