AIMC Topic: Liver
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Machine learning approaches for the prediction of postoperative complication risk in liver resection patients.
BMC medical informatics and decision making
Dec 30, 2021
BACKGROUND: For liver cancer patients, the occurrence of postoperative complications increases the difficulty of perioperative nursing, prolongs the hospitalization time of patients, and leads to large increases in hospitalization costs. The ability ...
Deep Learning in the Classification of Stage of Liver Fibrosis in Chronic Hepatitis B with Magnetic Resonance ADC Images.
Contrast media & molecular imaging
Dec 22, 2021
Liver fibrosis in chronic hepatitis B is the pathological repair response of the liver to chronic injury, which is a key step in the development of various chronic liver diseases to cirrhosis and an important link affecting the prognosis of chronic l...
Predictive Model for Drug-Induced Liver Injury Using Deep Neural Networks Based on Substructure Space.
Molecules (Basel, Switzerland)
Dec 13, 2021
Drug-induced liver injury (DILI) is a major concern for drug developers, regulators, and clinicians. However, there is no adequate model system to assess drug-associated DILI risk in humans. In the big data era, computational models are expected to p...
Robotic donor hepatectomy: A major breakthrough in living donor liver transplantation.
American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
Dec 6, 2021
Living donation in many countries is the main resource of organs. Healthy, volunteering individuals deserve the highest safety standards possible in addition to the least invasive technique to procure the organs. Since the introduction of living dono...
Displacement detection with sub-pixel accuracy and high spatial resolution using deep learning.
Journal of medical ultrasonics (2001)
Nov 27, 2021
PURPOSE: The purpose of this study was to detect two dimensional and sub-pixel displacement with high spatial resolution using an ultrasonic diagnostic apparatus. Conventional displacement detection methods assume neighborhood uniformity and cannot a...
Direct pixel to pixel principal strain mapping from tagging MRI using end to end deep convolutional neural network (DeepStrain).
Scientific reports
Nov 26, 2021
Regional soft tissue mechanical strain offers crucial insights into tissue's mechanical function and vital indicators for different related disorders. Tagging magnetic resonance imaging (tMRI) has been the standard method for assessing the mechanical...
A study of generalization and compatibility performance of 3D U-Net segmentation on multiple heterogeneous liver CT datasets.
BMC medical imaging
Nov 24, 2021
BACKGROUND: Most existing algorithms have been focused on the segmentation from several public Liver CT datasets scanned regularly (no pneumoperitoneum and horizontal supine position). This study primarily segmented datasets with unconventional liver...
A deep-learning-based prediction model for the biodistribution of Y microspheres in liver radioembolization.
Medical physics
Oct 21, 2021
BACKGROUND: Radioembolization with Y microspheres is a treatment approach for liver cancer. Currently, employed dosimetric calculations exhibit low accuracy, lacking consideration of individual patient, and tissue characteristics.
Preliminary study of generalized semiautomatic segmentation for 3D voxel labeling of lesions based on deep learning.
International journal of computer assisted radiology and surgery
Oct 15, 2021
PURPOSE: The three-dimensional (3D) voxel labeling of lesions requires significant radiologists' effort in the development of computer-aided detection software. To reduce the time required for the 3D voxel labeling, we aimed to develop a generalized ...
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