AI Medical Compendium Journal:
Technology in cancer research & treatment

Showing 41 to 50 of 65 articles

LCDAE: Data Augmented Ensemble Framework for Lung Cancer Classification.

Technology in cancer research & treatment Jan 1, 2022
The only possible solution to increase the patients' fatality rate is lung cancer early-stage detection. Recently, deep learning techniques became the most promising methods in medical image analysis compared with other numerous computer-aided diagn...
Humans Neural Networks, Computer Lung Lung Neoplasms Early Detection of Cancer
View on PubMed DOI

Deep Learning for Patient-Specific Quality Assurance: Predicting Gamma Passing Rates for IMRT Based on Delivery Fluence Informed by log Files.

Technology in cancer research & treatment Jan 1, 2022
In this study, we propose a deep learning-based approach to predict Intensity-modulated radiation therapy (IMRT) quality assurance (QA) gamma passing rates using delivery fluence informed by log files. A total of 112 IMRT plans for chest cancers we...
Particle Accelerators Humans Quality Assurance, Health Care Deep Learning Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted Radiotherapy, Intensity-Modulated Radiometry
View on PubMed DOI

Deep Learning-Based Internal Target Volume (ITV) Prediction Using Cone-Beam CT Images in Lung Stereotactic Body Radiotherapy.

Technology in cancer research & treatment Jan 1, 2022
This study aims to develop a deep learning (DL)-based (Mask R-CNN) method to predict the internal target volume (ITV) in cone beam computed tomography (CBCT) images for lung stereotactic body radiotherapy (SBRT) patients and to evaluate the predictio...
Radiosurgery Four-Dimensional Computed Tomography Humans Lung Deep Learning Cone-Beam Computed Tomography Lung Neoplasms Radiotherapy Planning, Computer-Assisted Respiration
View on PubMed DOI

Diagnostic Performance of AI for Cancers Registered in A Mammography Screening Program: A Retrospective Analysis.

Technology in cancer research & treatment Jan 1, 2022
To evaluate the performance of an artificial intelligence (AI) algorithm in a simulated screening setting and its effectiveness in detecting missed and interval cancers. Digital mammograms were collected from Bahcesehir Mammographic Screening Progr...
Retrospective Studies Female Risk Factors Breast Neoplasms Humans Artificial Intelligence Early Detection of Cancer Population Surveillance Mammography Turkey Risk Assessment ROC Curve Image Processing, Computer-Assisted Mass Screening
View on PubMed DOI

Cone Beam CT (CBCT) Based Synthetic CT Generation Using Deep Learning Methods for Dose Calculation of Nasopharyngeal Carcinoma Radiotherapy.

Technology in cancer research & treatment Jan 1, 2021
To generate synthetic CT (sCT) images with high quality from CBCT and planning CT (pCT) for dose calculation by using deep learning methods. 169 NPC patients with a total of 20926 slices of CBCT and pCT images were included. In this study the Cycle...
Middle Aged Radiotherapy Dosage Deep Learning Aged Nasopharyngeal Carcinoma Humans Adolescent Image Processing, Computer-Assisted Young Adult Radiotherapy, Image-Guided Cone-Beam Computed Tomography Algorithms Neoplasm Staging Adult Female Neoplasm Grading Male Radiotherapy Planning, Computer-Assisted
View on PubMed DOI

Colorectal Cancer Detected by Machine Learning Models Using Conventional Laboratory Test Data.

Technology in cancer research & treatment Jan 1, 2021
Current diagnostic methods for colorectal cancer (CRC) are colonoscopy and sigmoidoscopy, which are invasive and complex procedures with possible complications. This study aimed to determine models for CRC identification that involve minimally invas...
Logistic Models Support Vector Machine Area Under Curve Diagnostic Tests, Routine Machine Learning Retrospective Studies Electronic Health Records Female Male Aged Humans Middle Aged Adult Case-Control Studies Colorectal Neoplasms ROC Curve Biomarkers, Tumor
View on PubMed DOI

Prognosticating Outcome in Pancreatic Head Cancer With the use of a Machine Learning Algorithm.

Technology in cancer research & treatment Jan 1, 2021
The purpose of this project is to identify prognostic features in resectable pancreatic head adenocarcinoma and use these features to develop a machine learning algorithm that prognosticates survival for patients pursuing pancreaticoduodenectomy. A...
Retrospective Studies Female Survival Rate Male Adenocarcinoma Follow-Up Studies Pancreatic Neoplasms Pancreaticoduodenectomy Humans Machine Learning Algorithms Prognosis
View on PubMed DOI

Monte Carlo Dose Calculation Using MRI Based Synthetic CT Generated by Fully Convolutional Neural Network for Gamma Knife Radiosurgery.

Technology in cancer research & treatment Jan 1, 2021
The aim of this work is to study the dosimetric effect from generated synthetic computed tomography (sCT) from magnetic resonance (MR) images using a deep learning algorithm for Gamma Knife (GK) stereotactic radiosurgery (SRS). The Monte Carlo (MC) m...
Magnetic Resonance Imaging Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy, Intensity-Modulated Tomography, X-Ray Computed Radiotherapy Dosage Radiosurgery Neoplasms Monte Carlo Method Deep Learning Humans Phantoms, Imaging Image Processing, Computer-Assisted Neural Networks, Computer Prognosis Retrospective Studies
View on PubMed DOI

Differentiation of Intrahepatic Cholangiocarcinoma and Hepatic Lymphoma Based on Radiomics and Machine Learning in Contrast-Enhanced Computer Tomography.

Technology in cancer research & treatment Jan 1, 2021
This study aimed to explore the ability of texture parameters combining with machine learning methods in distinguishing intrahepatic cholangiocarcinoma (ICCA) and hepatic lymphoma (HL). A total of 28 patients with HL and 101 patients with ICCA were...
Tumor Burden Bile Duct Neoplasms Cholangiocarcinoma Radiographic Image Enhancement Male Middle Aged ROC Curve Image Processing, Computer-Assisted Lymphoma Contrast Media Diagnosis, Differential Neoplasm Grading Tomography, X-Ray Computed Female Reproducibility of Results Aged Humans Machine Learning Algorithms
View on PubMed DOI

Clinical Target Volume Auto-Segmentation of Esophageal Cancer for Radiotherapy After Radical Surgery Based on Deep Learning.

Technology in cancer research & treatment Jan 1, 2021
Radiotherapy plays an important role in controlling the local recurrence of esophageal cancer after radical surgery. Segmentation of the clinical target volume is a key step in radiotherapy treatment planning, but it is time-consuming and operator-de...
Humans Neural Networks, Computer Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Esophageal Neoplasms Radiotherapy Planning, Computer-Assisted Automation
View on PubMed DOI
Popular Topics
Popular Journals