AIMC Topic: Liver Neoplasms

Clear Filters Showing 621 to 630 of 838 articles

Neural Networks for Deep Radiotherapy Dose Analysis and Prediction of Liver SBRT Outcomes.

IEEE journal of biomedical and health informatics
Stereotactic body radiation therapy (SBRT) is a relatively novel treatment modality, with little post-treatment prognostic information reported. This study proposes a novel neural network based paradigm for accurate prediction of liver SBRT outcomes....

Beamforming and Speckle Reduction Using Neural Networks.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
With traditional beamforming methods, ultrasound B-mode images contain speckle noise caused by the random interference of subresolution scatterers. In this paper, we present a framework for using neural networks to beamform ultrasound channel signals...

Real-time tumor tracking using fluoroscopic imaging with deep neural network analysis.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: To improve respiratory gating accuracy and treatment throughput, we developed a fluoroscopic markerless tumor tracking algorithm based on a deep neural network (DNN).

Dynamic Regulation of Level Set Parameters Using 3D Convolutional Neural Network for Liver Tumor Segmentation.

Journal of healthcare engineering
Segmentation of liver tumors plays an important role in the choice of therapeutic strategies for liver disease and treatment monitoring. In this paper, we generalize the process of a level set with a novel algorithm of dynamic regulation to energy fu...

Predicting overall survival of patients with hepatocellular carcinoma using a three-category method based on DNA methylation and machine learning.

Journal of cellular and molecular medicine
Hepatocellular carcinoma (HCC) is closely associated with abnormal DNA methylation. In this study, we analyzed 450K methylation chip data from 377 HCC samples and 50 adjacent normal samples in the TCGA database. We screened 47,099 differentially meth...

Machine Learning-based Analysis of Rectal Cancer MRI Radiomics for Prediction of Metachronous Liver Metastasis.

Academic radiology
RATIONALE AND OBJECTIVES: To use machine learning-based magnetic resonance imaging radiomics to predict metachronous liver metastases (MLM) in patients with rectal cancer.

Using natural language processing to extract clinically useful information from Chinese electronic medical records.

International journal of medical informatics
AIMS: To develop a natural language processing (NLP)-based algorithm for extracting clinically useful information for patients with hepatocellular carcinoma (HCC) from Chinese electronic medical records (EMRs) and use these data for the assessment of...

Design and synthesis of new phthalazine-based derivatives as potential EGFR inhibitors for the treatment of hepatocellular carcinoma.

Bioorganic chemistry
Searching for new leads in the battle of cancer will never ends, we herein disclose the design and synthesis of new phthalazine derivatives and their in vitro and in vivo testing for their antiproliferative activity. Phthalazine was selected as a pri...

DeepM6ASeq: prediction and characterization of m6A-containing sequences using deep learning.

BMC bioinformatics
BACKGROUND: N6-methyladensine (m6A) is a common and abundant RNA methylation modification found in various species. As a type of post-transcriptional methylation, m6A plays an important role in diverse RNA activities such as alternative splicing, an ...