Katherine E. Link
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View article: The Brain Tumor Segmentation - Metastases (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI.
The Brain Tumor Segmentation - Metastases (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI. Open
The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchma…
View article: Best Practices for Large Language Models in Radiology
Best Practices for Large Language Models in Radiology Open
At the heart of radiological practice is the challenge of integrating complex imaging data with clinical information to produce actionable insights. Nuanced application of language is key for various activities, including managing requests…
View article: P10.02.A A NOVEL APPROACH CONCERNING MEDICAL EDUCATION ON AI AND ML THROUGH THE ASNR MICCAI BRATS 2023 BRAIN METASTASES CHALLENGE
P10.02.A A NOVEL APPROACH CONCERNING MEDICAL EDUCATION ON AI AND ML THROUGH THE ASNR MICCAI BRATS 2023 BRAIN METASTASES CHALLENGE Open
BACKGROUND Artificial intelligence (AI) and machine learning (ML) are in the process of being integrated into modern healthcare, especially in imaging data-dependent fields like Radiology. Unfortunately, data shows that the acquaintance of…
View article: Longitudinal deep neural networks for assessing metastatic brain cancer on a large open benchmark
Longitudinal deep neural networks for assessing metastatic brain cancer on a large open benchmark Open
The detection and tracking of metastatic cancer over the lifetime of a patient remains a major challenge in clinical trials and real-world care. Advances in deep learning combined with massive datasets may enable the development of tools t…
View article: The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI
The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI Open
The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchma…
View article: Longitudinal deep neural networks for assessing metastatic brain cancer on a massive open benchmark.
Longitudinal deep neural networks for assessing metastatic brain cancer on a massive open benchmark. Open
The detection and tracking of metastatic cancer over the lifetime of a patient remains a major challenge in clinical trials and real-world care. 1–3 Recent advances in deep learning combined with massive, real-world datasets may enable the…
View article: RadImageNet: An Open Radiologic Deep Learning Research Dataset for Effective Transfer Learning
RadImageNet: An Open Radiologic Deep Learning Research Dataset for Effective Transfer Learning Open
RadImageNet pretrained models demonstrated better interpretability compared with ImageNet models, especially for smaller radiologic datasets.Keywords: CT, MR Imaging, US, Head/Neck, Thorax, Brain/Brain Stem, Evidence-based Medicine, Comput…
View article: RadImageNet: A Large-scale Radiologic Dataset for Enhancing Deep Learning Transfer Learning Research
RadImageNet: A Large-scale Radiologic Dataset for Enhancing Deep Learning Transfer Learning Research Open
Most current medical imaging Artificial Intelligence (AI) relies upon transfer learning using convolutional neural networks (CNNs) created using ImageNet, a large database of natural world images, including cats, dogs, and vehicles. Size, …
View article: Human cortical expansion involves diversification and specialization of supragranular intratelencephalic-projecting neurons
Human cortical expansion involves diversification and specialization of supragranular intratelencephalic-projecting neurons Open
The neocortex is disproportionately expanded in human compared to mouse, both in its total volume relative to subcortical structures and in the proportion occupied by supragranular layers that selectively make connections within the cortex…
View article: Toward an integrated classification of neuronal cell types: morphoelectric and transcriptomic characterization of individual GABAergic cortical neurons
Toward an integrated classification of neuronal cell types: morphoelectric and transcriptomic characterization of individual GABAergic cortical neurons Open
Neurons are frequently classified into distinct groups or cell types on the basis of structural, physiological, or genetic attributes. To better constrain the definition of neuronal cell types, we characterized the transcriptomes and intri…
View article: The Neural Basis of Approach-Avoidance Conflict: A Model Based Analysis
The Neural Basis of Approach-Avoidance Conflict: A Model Based Analysis Open
Approach-avoidance conflict arises when the drives to pursue reward and avoid harm are incompatible. Previous neuroimaging studies of approach-avoidance conflict have shown large variability in reported neuroanatomical correlates. These pr…