Oncology/Hematology

Automatic Prediction of MGMT Status in Glioblastoma via Deep Learning-Based MR Image Analysis.

Methylation of the O-methylguanine methyltransferase (MGMT) gene promoter is correlated with the effectiveness of the current standard of care in glioblastoma patients. In this study, a deep learning pipeline is designed for automatic prediction of MGMT status in 87 glioblastoma patients with contrast-enhanced T1W images and 66 with fluid-attenuated inversion recovery(FLAIR) images. The end-to-end...

Performance of a Deep Learning Algorithm Compared with Radiologic Interpretation for Lung Cancer Detection on Chest Radiographs in a Health Screening Population.

Background The performance of a deep learning algorithm for lung cancer detection on chest radiographs in a health screening population is unknown. Purpose To validate a commercially available deep learning algorithm for lung cancer detection on chest radiographs in a health screening population. Materials and Methods Out-of-sample testing of a deep learning algorithm was retrospectively performed...

A data-driven approach to a chemotherapy recommendation model based on deep learning for patients with colorectal cancer in Korea.

BACKGROUND: Clinical Decision Support Systems (CDSSs) have recently attracted attention as a method for minimizing medical errors. Existing CDSSs are ...

Detecting mouse squamous cell carcinoma from submicron full-field optical coherence tomography images by deep learning.

The standard medical practice for cancer diagnosis requires histopathology, which is an invasive and time-consuming procedure. Optical coherence tomog...

Deep Learning to Estimate RECIST in Patients with NSCLC Treated with PD-1 Blockade.

Real-world evidence (RWE), conclusions derived from analysis of patients not treated in clinical trials, is increasingly recognized as an opportunity ...

Microscopic brain tumor detection and classification using 3D CNN and feature selection architecture.

Brain tumor is one of the most dreadful natures of cancer and caused a huge number of deaths among kids and adults from the past few years. According ...

The utility of a deep learning-based algorithm for bone scintigraphy in patient with prostate cancer.

OBJECTIVE: Bone scintigraphy has often been used to evaluate bone metastases. Its functionality is evident in detecting bone metastasis in patients wi...

Transcription factor expression as a predictor of colon cancer prognosis: a machine learning practice.

BACKGROUND: Colon cancer is one of the leading causes of cancer deaths in the USA and around the world. Molecular level characters, such as gene expre...

Artificial Intelligence and Deep Learning in Neuroradiology: Exploring the New Frontier.

There have been many recently published studies exploring machine learning (ML) and deep learning applications within neuroradiology. The improvement ...

Prediction of early recurrence of hepatocellular carcinoma after resection using digital pathology images assessed by machine learning.

Hepatocellular carcinoma (HCC) is a representative primary liver cancer caused by long-term and repetitive liver injury. Surgical resection is general...

Robotic Resection of Postero-Superior Liver Segments (7,8) (with Video).

BACKGROUND: Surgical resection is the standard treatment for colorectal liver metastases. Parenchyma-sparing technique should always be attemptedto pr...

Brain tumor segmentation using 3D Mask R-CNN for dynamic susceptibility contrast enhanced perfusion imaging.

The segmentation of neoplasms is an important part of radiotherapy treatment planning, monitoring disease progression, and predicting patient outcome....

Cancer gene expression profiles associated with clinical outcomes to chemotherapy treatments.

BACKGROUND: Machine learning (ML) methods still have limited applicability in personalized oncology due to low numbers of available clinically annotat...

Editorial for "MRI-Based Deep Learning Model for Distant Metastasis-Free Survival in Locoregionally Advanced Nasopharyngeal Carcinoma".

GP-GAN: Brain tumor growth prediction using stacked 3D generative adversarial networks from longitudinal MR Images.

Brain tumors are one of the major common causes of cancer-related death, worldwide. Growth prediction of these tumors, particularly gliomas which are ...

A comprehensive review of deep learning in colon cancer.

Deep learning has emerged as a leading machine learning tool in object detection and has attracted attention with its achievements in progressing medi...

Simple low-cost approaches to semantic segmentation in radiation therapy planning for prostate cancer using deep learning with non-contrast planning CT images.

PURPOSE: Deep learning has shown great efficacy for semantic segmentation. However, there are difficulties in the collection, labeling and management ...

Myricitrin inhibits vascular endothelial growth factor-induced angiogenesis of human umbilical vein endothelial cells and mice.

In the present study, the protective effects of myricitrin against vascular endothelial growth factor (VEGF)-induced angiogenesis of vascular endothel...

Liver imaging features by convolutional neural network to predict the metachronous liver metastasis in stage I-III colorectal cancer patients based on preoperative abdominal CT scan.

BACKGROUND: Introducing deep learning approach to medical images has rendered a large amount of un-decoded information into usage in clinical research...

Convolutional neural networks versus radiologists in characterization of small hypoattenuating hepatic nodules on CT: a critical diagnostic challenge in staging of colorectal carcinoma.

Our objective was to compare the diagnostic performance and diagnostic confidence of convolutional neural networks (CNN) to radiologists in characteri...