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Medical & Biological Engineering & Computing|May 3, 2024
SleepBoost: a multi-level tree-based ensemble model for automatic sleep stage classificationAkib Zaman, Shiu Kumar, Swakkhar Shatabda, et al.
Medical & Biological Engineering & Computing|April 18, 2024
Tissue specific tumor-gene link prediction through sampling based GNN using a heterogeneous networkSurabhi Mishra, Gurjot Singh, Mahua Bhattacharya
Medical & Biological Engineering & Computing|January 9, 2024
Automatic segmentation of layers in chorio-retinal complex using Graph-based method for ultra-speed 1.7 MHz wide field swept source FDML optical coherence tomographyRaju Poddar, Vinita Shukla, Zoya Alam, et al.
Medical & Biological Engineering & Computing|December 15, 2023
Improving signal-to-noise ratio by maximal convolution of longitudinal and transverse magnetization components in MRI: application to the breast cancer detectionMansour Ashoor, Abdollah Khorshidi
Medical & Biological Engineering & Computing|December 29, 2023
MD-UNet: a medical image segmentation network based on mixed depthwise convolutionYun Liu, Shuanglong Yao, Xing Wang, et al.
Medical & Biological Engineering & Computing|December 30, 2023
Multi-energy CT material decomposition using graph model improved CNNZaifeng Shi, Fanning Kong, Ming Cheng, et al.
Medical & Biological Engineering & Computing|January 3, 2024
SALW-Net: a lightweight convolutional neural network based on self-adjusting loss function for spine MR image segmentationSiyuan He, Qi Li, Xianda Li, et al.
Medical & Biological Engineering & Computing|August 2, 2022
Using convolutional neural network to analyze brain MRI images for predicting functional outcomes of strokeYu-Liang Lai, Yu-Dan Wu, Huan-Jui Yeh, et al.
Medical & Biological Engineering & Computing|October 7, 2022
Nanotechnology and quantum science enabled advances in neurological medical applications: diagnostics and treatmentsSadia Batool, Hafezeh Nabipour, Seeram Ramakrishna, et al.
Medical & Biological Engineering & Computing|January 26, 2023
Artificial intelligence and machine learning as a viable solution for hip implant failure diagnosis-Review of literature and in vitro case studyRemya Ampadi Ramachandran, Sheng-Wei Chi, P Srinivasa Pai, et al.
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