Machine learning for medical imaging: methodological failures and recommendations for the future
Research in computer analysis of medical images bears many promises to improve patients'
health. However, a number of systematic challenges are slowing down the progress of the …
health. However, a number of systematic challenges are slowing down the progress of the …
Establishment of best practices for evidence for prediction: a review
Importance Great interest exists in identifying methods to predict neuropsychiatric disease
states and treatment outcomes from high-dimensional data, including neuroimaging and …
states and treatment outcomes from high-dimensional data, including neuroimaging and …
The promise of machine learning in predicting treatment outcomes in psychiatry
For many years, psychiatrists have tried to understand factors involved in response to
medications or psychotherapies, in order to personalize their treatment choices. There is …
medications or psychotherapies, in order to personalize their treatment choices. There is …
What is the test-retest reliability of common task-functional MRI measures? New empirical evidence and a meta-analysis
Identifying brain biomarkers of disease risk is a growing priority in neuroscience. The ability
to identify meaningful biomarkers is limited by measurement reliability; unreliable measures …
to identify meaningful biomarkers is limited by measurement reliability; unreliable measures …
Imaging structural and functional brain development in early childhood
In humans, the period from term birth to∼ 2 years of age is characterized by rapid and
dynamic brain development and plays an important role in cognitive development and risk of …
dynamic brain development and plays an important role in cognitive development and risk of …
How to establish robust brain–behavior relationships without thousands of individuals
Can studying individual differences in brain structure and function reveal individual
differences in behavior? Analyses of MRI data from nearly 50,000 individuals may suggest …
differences in behavior? Analyses of MRI data from nearly 50,000 individuals may suggest …
Machine learning for precision psychiatry: opportunities and challenges
The nature of mental illness remains a conundrum. Traditional disease categories are
increasingly suspected to misrepresent the causes underlying mental disturbance. Yet …
increasingly suspected to misrepresent the causes underlying mental disturbance. Yet …
A distributed fMRI-based signature for the subjective experience of fear
The specific neural systems underlying the subjective feeling of fear are debated in affective
neuroscience. Here, we combine functional MRI with machine learning to identify and …
neuroscience. Here, we combine functional MRI with machine learning to identify and …
Cross-validation failure: Small sample sizes lead to large error bars
G Varoquaux - Neuroimage, 2018 - Elsevier
Predictive models ground many state-of-the-art developments in statistical brain image
analysis: decoding, MVPA, searchlight, or extraction of biomarkers. The principled approach …
analysis: decoding, MVPA, searchlight, or extraction of biomarkers. The principled approach …
Discovery and validation of biomarkers to aid the development of safe and effective pain therapeutics: challenges and opportunities
Pain medication plays an important role in the treatment of acute and chronic pain
conditions, but some drugs, opioids in particular, have been overprescribed or prescribed …
conditions, but some drugs, opioids in particular, have been overprescribed or prescribed …