AIMC Topic: Liver
Clear Filters Showing 111 to 120 of 589 articles
Comprehensive machine learning models for predicting therapeutic targets in type 2 diabetes utilizing molecular and biochemical features in rats.
Frontiers in endocrinology
May 24, 2024
INTRODUCTION: With the increasing prevalence of type 2 diabetes mellitus (T2DM), there is an urgent need to discover effective therapeutic targets for this complex condition. Coding and non-coding RNAs, with traditional biochemical parameters, have s...
CMAN: Cascaded Multi-scale Spatial Channel Attention-guided Network for large 3D deformable registration of liver CT images.
Medical image analysis
May 22, 2024
Deformable image registration is an essential component of medical image analysis and plays an irreplaceable role in clinical practice. In recent years, deep learning-based registration methods have demonstrated significant improvements in convenienc...
Automated segmentation of liver and hepatic vessels on portal venous phase computed tomography images using a deep learning algorithm.
Journal of applied clinical medical physics
May 21, 2024
BACKGROUND: CT-image segmentation for liver and hepatic vessels can facilitate liver surgical planning. However, time-consuming process and inter-observer variations of manual segmentation have limited wider application in clinical practice.
Hepatic toxicity prediction of bisphenol analogs by machine learning strategy.
The Science of the total environment
May 21, 2024
Toxicological studies have demonstrated the hepatic toxicity of several bisphenol analogs (BPs), a prevalent type of endocrine disruptor. The development of Adverse Outcome Pathway (AOP) has substantially contributed to the rapid risk assessment for ...
ResTransUnet: An effective network combined with Transformer and U-Net for liver segmentation in CT scans.
Computers in biology and medicine
May 21, 2024
Liver segmentation is a fundamental prerequisite for the diagnosis and surgical planning of hepatocellular carcinoma. Traditionally, the liver contour is drawn manually by radiologists using a slice-by-slice method. However, this process is time-cons...
Deep learning and digital pathology powers prediction of HCC development in steatotic liver disease.
Hepatology (Baltimore, Md.)
May 20, 2024
BACKGROUND AND AIMS: Identifying patients with steatotic liver disease who are at a high risk of developing HCC remains challenging. We present a deep learning (DL) model to predict HCC development using hematoxylin and eosin-stained whole-slide imag...
A novel support vector machine-based 1-day, single-dose prediction model of genotoxic hepatocarcinogenicity in rats.
Archives of toxicology
May 18, 2024
The development of a rapid and accurate model for determining the genotoxicity and carcinogenicity of chemicals is crucial for effective cancer risk assessment. This study aims to develop a 1-day, single-dose model for identifying genotoxic hepatocar...
Points of interest linear attention network for real-time non-rigid liver volume to surface registration.
Medical physics
May 17, 2024
BACKGROUND: In laparoscopic liver surgery, accurately predicting the displacement of key intrahepatic anatomical structures is crucial for informing the doctor's intraoperative decision-making. However, due to the constrained surgical perspective, on...
Multimodality quantitative ultrasound envelope statistics imaging based support vector machines for characterizing tissue scatterer distribution patterns: Methods and application in detecting microwave-induced thermal lesions.
Ultrasonics sonochemistry
May 17, 2024
Ultrasound envelope statistics imaging, including ultrasound Nakagami imaging, homodyned-K imaging, and information entropy imaging, is an important group of quantitative ultrasound techniques for characterizing tissue scatterer distribution patterns...
Accelerated Diffusion-Weighted Magnetic Resonance Imaging of the Liver at 1.5 T With Deep Learning-Based Image Reconstruction: Impact on Image Quality and Lesion Detection.
Journal of computer assisted tomography
May 6, 2024
OBJECTIVE: To perform image quality comparison between deep learning-based multiband diffusion-weighted sequence (DL-mb-DWI), accelerated multiband diffusion-weighted sequence (accelerated mb-DWI), and conventional multiband diffusion-weighted sequen...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31032
- Neural Networks, Computer 29717
- Algorithms 26831
- Deep Learning 26345
- Artificial Intelligence 24290
- Robotics 13311
- Image Processing, Computer-Assisted 9521
- Retrospective Studies 9110
- Magnetic Resonance Imaging 6181
- Reproducibility of Results 5592
- Tomography, X-Ray Computed 4770
- Support Vector Machine 4686
- Computational Biology 4236
- Brain 4050
- Computer Simulation 3881
Recent Journals
- Scientific reports 5940
- Sensors (Basel, Switzerland) 4794
- PloS one 4015
- Neural networks : the official journal of the International Neural Network Society 2929
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1854
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1130
- Journal of chemical information and modeling 998
- Nature communications 943
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 853
- IEEE transactions on neural networks and learning systems 826