Data-driven machine learning (ML) has emerged as a promising approach for building accurate and robust statistical models from medical data, which is collected in huge volumes …
Psilocybin therapy shows antidepressant potential, but its therapeutic actions are not well understood. We assessed the subacute impact of psilocybin on brain function in two clinical …
Worldwide, there are nearly 10 million new cases of dementia annually, of which Alzheimer's disease (AD) is the most common. New measures are needed to improve the …
Conventional multiview clustering seeks to partition data into respective groups based on the assumption that all views are fully observed. However, in practical applications, such as …
Artificial intelligence (AI) continues to garner substantial interest in medical imaging. The potential applications are vast and include the entirety of the medical imaging life cycle from …
Deep reinforcement learning augments the reinforcement learning framework and utilizes the powerful representation of deep neural networks. Recent works have demonstrated the …
With the advances of data-driven machine learning research, a wide variety of prediction problems have been tackled. It has become critical to explore how machine learning and …
M Liu, F Li, H Yan, K Wang, Y Ma, L Shen, M Xu… - Neuroimage, 2020 - Elsevier
Alzheimer's disease (AD) is a progressive and irreversible brain degenerative disorder. Mild cognitive impairment (MCI) is a clinical precursor of AD. Although some treatments can …
The current research paradigm for Huntington's disease is based on participants with overt clinical phenotypes and does not address its pathophysiology nor the biomarker changes …