Clinical impact and quality of randomized controlled trials involving interventions evaluating artificial intelligence prediction tools: a systematic review
Q Zhou, Z Chen, Y Cao, S Peng - NPJ digital medicine, 2021 - nature.com
The evidence of the impact of traditional statistical (TS) and artificial intelligence (AI) tool
interventions in clinical practice was limited. This study aimed to investigate the clinical …
interventions in clinical practice was limited. This study aimed to investigate the clinical …
Transfer learning in magnetic resonance brain imaging: A systematic review
(1) Background: Transfer learning refers to machine learning techniques that focus on
acquiring knowledge from related tasks to improve generalization in the tasks of interest. In …
acquiring knowledge from related tasks to improve generalization in the tasks of interest. In …
Replicable brain–phenotype associations require large-scale neuroimaging data
Numerous neuroimaging studies have investigated the neural basis of interindividual
differences but the replicability of brain–phenotype associations remains largely unknown …
differences but the replicability of brain–phenotype associations remains largely unknown …
No free lunch from deep learning in neuroscience: A case study through models of the entorhinal-hippocampal circuit
Research in Neuroscience, as in many scientific disciplines, is undergoing a renaissance
based on deep learning. Unique to Neuroscience, deep learning models can be used not …
based on deep learning. Unique to Neuroscience, deep learning models can be used not …
Deep learning-based brain age prediction in normal aging and dementia
Brain aging is accompanied by patterns of functional and structural change. Alzheimer's
disease (AD), a representative neurodegenerative disease, has been linked to accelerated …
disease (AD), a representative neurodegenerative disease, has been linked to accelerated …
[HTML][HTML] A dynamic graph convolutional neural network framework reveals new insights into connectome dysfunctions in ADHD
The pathological mechanism of attention deficit hyperactivity disorder (ADHD) is
incompletely specified, which leads to difficulty in precise diagnosis. Functional magnetic …
incompletely specified, which leads to difficulty in precise diagnosis. Functional magnetic …
A perspective on brain-age estimation and its clinical promise
Brain-age estimation has gained increased attention in the neuroscientific community owing
to its potential use as a biomarker of brain health. The difference between estimated and …
to its potential use as a biomarker of brain health. The difference between estimated and …
[HTML][HTML] Machine learning prediction of cognition from functional connectivity: Are feature weights reliable?
Cognitive performance can be predicted from an individual's functional brain connectivity
with modest accuracy using machine learning approaches. As yet, however, predictive …
with modest accuracy using machine learning approaches. As yet, however, predictive …
Modern views of machine learning for precision psychiatry
In light of the National Institute of Mental Health (NIMH)'s Research Domain Criteria (RDoC),
the advent of functional neuroimaging, novel technologies and methods provide new …
the advent of functional neuroimaging, novel technologies and methods provide new …
[HTML][HTML] Deep neural networks learn general and clinically relevant representations of the ageing brain
The discrepancy between chronological age and the apparent age of the brain based on
neuroimaging data—the brain age delta—has emerged as a reliable marker of brain health …
neuroimaging data—the brain age delta—has emerged as a reliable marker of brain health …