首页|Department of Informatics Reports Findings in Esophageal Cancer (Layer-selective deep representation to improve esophageal cancer classification)
Department of Informatics Reports Findings in Esophageal Cancer (Layer-selective deep representation to improve esophageal cancer classification)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Oncology-Esophageal Cancer is the subject of a report. According to news reporting originating from Vitoria, Brazil, by NewsRx correspondents, research stated, "Even though artific ial intelligence and machine learning have demonstrated remarkable performances in medical image computing, their accountability and transparency level must be improved to transfer this success into clinical practice. The reliability of mac hine learning decisions must be explained and interpreted, especially for suppor ting the medical diagnosis." Our news editors obtained a quote from the research from the Department of Infor matics, "For this task, the deep learning techniques' black-box nature must some how be lightened up to clarify its promising results. Hence, we aim to investiga te the impact of the ResNet-50 deep convolutional design for Barrett's esophagus and adenocarcinoma classification. For such a task, and aiming at proposing a t wo-step learning technique, the output of each convolutional layer that composes the ResNet-50 architecture was trained and classified for further definition of layers that would provide more impact in the architecture. We showed that local information and high-dimensional features are essential to improve the classifi cation for our task."
VitoriaBrazilSouth AmericaCancerCyborgsEmerging TechnologiesEsophageal CancerGastroenterologyHealth and MedicineMachine LearningOncology
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