Pathologists can label pathologies differently, making it challenging to yield consistent assessments in the absence of one ground truth. To address this problem, we present a deep learning (DL) approach that draws on a cohort of experts, weighs each contribution, and is robust to noisy labels. We collected 100,495 annotations on 20,099 candidate amyloid beta neuropathologies (cerebral amyloid angiopathy (CAA), and cored and diffuse plaques) from three institutions, independently annotated by five experts. DL methods trained on a consensus-of-two strategy yielded 12.6-26% improvements by area under the precision recall curve (AUPRC) when compared to those that learned individualized annotations. This strategy surpassed individual-expert mod...
Background: Cardiac magnetic resonance (CMR) is part of the diagnostic work-up for cardiac amyloidos...
Developing deep learning algorithms that extract rich representations could facilitate accurate diag...
“Alzheimer’s disease” (AD) is a neurodegenerative disorder in which the memory shrinks and neurons d...
Pathologists can label pathologies differently, making it challenging to yield consistent assessment...
Neuropathologists assess vast brain areas to identify diverse and subtly-differentiated morphologies...
Precise, scalable, and quantitative evaluation of whole slide images is crucial in neuropathology. W...
Abstract Traditionally, analysis of neuropathological markers in neurodegenerative diseases has reli...
Semi-quantitative scoring schemes like the Consortium to Establish a Registry for Alzheimer's Diseas...
Background and aim: Alzheimer's disease (AD) is a neurodegenerative disease that attacks the brain b...
Abstract Machine learning (ML) has increasingly been used to assist and expand current practices in ...
Background: Cardiovascular magnetic resonance (CMR) is part of the diagnostic work-up for cardiac am...
Background The three core pathologies of Alzheimer’s disease (AD) are amyloid pathol...
Background: Detailed pathology analysis and morphological quantification is tedious and prone to err...
The aim of this work was to compare the classification of cardiac MR-images of AL versus ATTR amyloi...
Heterogeneity of brain diseases is a challenge for precision diagnosis/prognosis. We describe and va...
Background: Cardiac magnetic resonance (CMR) is part of the diagnostic work-up for cardiac amyloidos...
Developing deep learning algorithms that extract rich representations could facilitate accurate diag...
“Alzheimer’s disease” (AD) is a neurodegenerative disorder in which the memory shrinks and neurons d...
Pathologists can label pathologies differently, making it challenging to yield consistent assessment...
Neuropathologists assess vast brain areas to identify diverse and subtly-differentiated morphologies...
Precise, scalable, and quantitative evaluation of whole slide images is crucial in neuropathology. W...
Abstract Traditionally, analysis of neuropathological markers in neurodegenerative diseases has reli...
Semi-quantitative scoring schemes like the Consortium to Establish a Registry for Alzheimer's Diseas...
Background and aim: Alzheimer's disease (AD) is a neurodegenerative disease that attacks the brain b...
Abstract Machine learning (ML) has increasingly been used to assist and expand current practices in ...
Background: Cardiovascular magnetic resonance (CMR) is part of the diagnostic work-up for cardiac am...
Background The three core pathologies of Alzheimer’s disease (AD) are amyloid pathol...
Background: Detailed pathology analysis and morphological quantification is tedious and prone to err...
The aim of this work was to compare the classification of cardiac MR-images of AL versus ATTR amyloi...
Heterogeneity of brain diseases is a challenge for precision diagnosis/prognosis. We describe and va...
Background: Cardiac magnetic resonance (CMR) is part of the diagnostic work-up for cardiac amyloidos...
Developing deep learning algorithms that extract rich representations could facilitate accurate diag...
“Alzheimer’s disease” (AD) is a neurodegenerative disorder in which the memory shrinks and neurons d...