Artificial Intelligence-assisted Detection Tool for Pancreatic Cancer - PANCREASaver
Summary PANCREASaver contains a “Pancreas Cancer (PC) automatic segmentation model” (image segmentation) and a “Pancreas Cancer (PC) analysis AI model” (image classification) that can read the DICOM format of postcontrast CT images directly for the automatic analysis process. After conducting prep-processing with image processing algorithms, C2FNAS is employed to illustrate the tumor position prior to the diagnosis conducted by CNN. The results can be provided to the physician for diagnostic reference so as to reduce early omissions and increase the detection rate of pancreatic cancer.
The overall five-year survival rate of pancreatic cancer is less than 10%, which turns it the most lethal cancer. However, if the tumor is detected and treated sooner when it is smaller than 2 cm, the five-year survival rate can be increased to 80%. PANCREASaver is the world’s first computer-assisted detection system that uses CNN models to detect pancreatic cancer on CT images and assists physicians when interpreting. It increases the tumor detection rate of pancreatic cancer on CT images and fulfills the urgent clinical needs of diagnosing pancreatic cancer that is often ignored on CT images.
PANCREASaver is the world's first AI pancreatic cancer (PC) detection model that can detect 92.1% of tumors <2 cm on CTs and assists physicians in interpretation to improve patient survival. The usage of abdominal CT scans is up to 920,000 per year in Taiwan, thus, a combination of PANCREASaver and CT scan is a possible new diagnostic tool that can create innovative medical services and business opportunities for medical institutions and physical examination centers. Besides, health insurance-related units can also benefit from saving the high medical expenses of advanced PC patients.
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Keyword Medical engineering and medical equipment Intelligent Information System#Interdisciplinary integration
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