Diabetic retinopathy (DR) is one of the most common eye conditions among diabetic patients.
Accurate automatic liver and tumor segmentation plays a vital role in treatment planning and disease monitoring.
Deep learning has achieved promising segmentation performance on 3D left atrium MR images.
We use the proposed criteria to select samples for strong and weak labelers to produce oracle labels and pseudo labels simultaneously at each active learning iteration in an ensemble learning manner, which can be examined with IoMT Platform.
Gene mutation prediction in hepatocellular carcinoma (HCC) is of great diagnostic and prognostic value for personalized treatments and precision medicine.
no code implementations • 8 May 2020 • Jiapan Gu, Ziyuan Zhao, Zeng Zeng, Yuzhe Wang, Zhengyiren Qiu, Bharadwaj Veeravalli, Brian Kim Poh Goh, Glenn Kunnath Bonney, Krishnakumar Madhavan, Chan Wan Ying, Lim Kheng Choon, Thng Choon Hua, Pierce KH Chow
Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and the fourth most common cause of cancer-related death worldwide.
Water quality has a direct impact on industry, agriculture, and public health.
Diabetic retinopathy (DR) is a common retinal disease that leads to blindness.
In this study, we applied powerful deep neural network and explored a process in the forecast of skeletal bone age with the specifically combine joints images to increase the performance accuracy compared with the whole hand images.