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ACR DSI Publishes Six New Neuroradiology AI Use Cases
Feb. 19, 2021
The ACR Data Science Institute® (ACR DSI) released six new neuroradiology use cases in February, adding substantially to the scenarios DSI provides to the artificial intelligence (AI) community. Developers can freely access 21 neuroradiology use cases on the DSI website.
“Practitioners are expressing tremendous enthusiasm for practical AI tools to improve neuroradiology diagnosis and treatment,” said Alexander Norbash, MD, MS, FACR Chair of the ACR DSI Neuroradiology Panel. “We believe through collaborations with data scientists and generating use cases, we will secure the role of AI algorithms in clinical practice. This is a crucial time to get involved with AI and bring more applications to clinical practice,” he said.
The use cases include disease detection and lesion quantification: Hemorrhagic Brain Contusion, Detection of Communicating Hydrocephalus, CSF Flow Quantification, White Matter Lesion Tracking in Multiple Sclerosis, Quantifying Carotid Stenosis on CTA and Identifying Non-Enhancing Infiltrative Tumor in High Grade Glioma .
ACR DSI use cases are scenarios describing where the use of AI will be beneficial in a clinical setting. They provide structured data elements for training, testing and monitoring algorithms to help those developing AI to create new AI models, or improve existing AI products.
“Practitioners are expressing tremendous enthusiasm for practical AI tools to improve neuroradiology diagnosis and treatment,” said Alexander Norbash, MD, MS, FACR Chair of the ACR DSI Neuroradiology Panel. “We believe through collaborations with data scientists and generating use cases, we will secure the role of AI algorithms in clinical practice. This is a crucial time to get involved with AI and bring more applications to clinical practice,” he said.
The use cases include disease detection and lesion quantification: Hemorrhagic Brain Contusion, Detection of Communicating Hydrocephalus, CSF Flow Quantification, White Matter Lesion Tracking in Multiple Sclerosis, Quantifying Carotid Stenosis on CTA and Identifying Non-Enhancing Infiltrative Tumor in High Grade Glioma .
ACR DSI use cases are scenarios describing where the use of AI will be beneficial in a clinical setting. They provide structured data elements for training, testing and monitoring algorithms to help those developing AI to create new AI models, or improve existing AI products.
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