Understanding the Turnaround Time Effects of an AI-based Prioritization System for Intracranial Hemorrhage
Intracranial hemorrhage (ICH) is a type of bleeding that happens inside the skull. Every year, 67,000 patients in the US suffer from ICH. Although ICH affects a small percentage of the population, it is a very serious condition—the 1-month mortality rate is 35% to 52% with nearly half of the resulting mortality occurring in the first 24 hours of onset .
This summer is an exciting time to be working in medical imaging AI. I have been thinking about three new developments that may have profound implications for patients, care delivery organizations, and medical AI developers in the months ahead.
CuraCloud’s most recent research paper entitled “Precise diagnosis of intracranial hemorrhage and subtypes using a three-dimensional joint convolutional and recurrent neural network” has been accepted for publication in European Radiology.
CuraCloud’s most recent research paper entitled “DeepCenterline: a Multi-task Fully Convolutional Network for Centerline Extraction” has been accepted for presentation at Information Processing in Medical Imaging (IPMI) 2019 in Hong Kong.
The problem addressed in this white paper is the challenge of applying formal systems development processes to collaborative development of Artificial Intelligence (AI) in healthcare.
Chest radiography or Chest X-ray (CXR), is one of the most powerful and commonly used imaging modalities in clinical settings.
CuraCloud’s AI Development Services supply medical imaging AI expertise and technical capabilities to healthcare organizations to create their own quality and productivity innovations.
Let's start something new together.