The Radiological Society of North America is conducting Abdominal Trauma Detection Hackathon 2023 to harness the power of artificial intelligence and machine learning and improve trauma care and patient outcomes worldwide. Check out the details below!
The Radiological Society of North America (RSNA) is a non-profit organization and an international society of radiologists, medical physicists and other medical imaging professionals representing 31 radiologic subspecialties from 145 countries around the world. Based in Oak Brook, Illinois, the Society was established in 1915. RSNA’s organizational mission is to promote excellence in patient care and health care delivery through education, research and technologic innovation.
Traumatic injury is the most common cause of death in the first four decades of life and a major public health problem around the world. There are estimated to be more than 5 million annual deaths worldwide from traumatic injury.
Prompt and accurate diagnosis of traumatic injuries is crucial for initiating appropriate and timely interventions, which can significantly improve patient outcomes and survival rates. Computed tomography (CT) has become an indispensable tool in evaluating patients with suspected abdominal injuries due to its ability to provide detailed cross-sectional images of the abdomen.
Interpreting CT scans for abdominal trauma, however, can be a complex and time-consuming task, especially when multiple injuries or areas of subtle active bleeding are present. This challenge seeks to harness the power of artificial intelligence and machine learning to assist medical professionals in rapidly and precisely detecting injuries and grading their severity. The development of advanced algorithms for this purpose has the potential to improve trauma care and patient outcomes worldwide.
Blunt force abdominal trauma is among the most common types of traumatic injury, with the most frequent cause being motor vehicle accidents. Abdominal trauma may result in damage and internal bleeding of the internal organs, including the liver, spleen, kidneys, and bowel. Detection and classification of injuries are key to effective treatment and favorable outcomes. A large proportion of patients with abdominal trauma require urgent surgery. Abdominal trauma often cannot be diagnosed clinically by physical exam, patient symptoms, or laboratory tests.
Prompt diagnosis of abdominal trauma using medical imaging is thus critical to patient care. AI tools that assist and expedite diagnosis of abdominal trauma have the potential to substantially improve patient care and health outcomes in the emergency setting.
The RSNA Abdominal Trauma Detection AI Challenge, organized by the RSNA in collaboration with the American Society of Emergency Radiology (ASER) and the Society for Abdominal Radiology (SAR), gives researchers the task of building models that detect severe injury to the internal abdominal organs, including the liver, kidneys, spleen, and bowel, as well as any active internal bleeding.
The hackathon is open to the Students, technologist, freelancers and professional developer community. To be eligible to enter the Competition, you must be:
Interested candidates can apply online via this link.
