Latest AI and machine learning research in other cancers for healthcare professionals.
BACKGROUND AND PURPOSE: To examine whether feature-fusion (FF) method improves single-shot detector'...
Predicting the response of patients with ulcerative colitis (UC) to a biologic such as vedolizumab (...
Pathology is practiced by visual inspection of histochemically stained tissue slides. While the hema...
Postoperative mammograms present interpretive challenges due to postoperative distortion and hemato...
PURPOSE: We propose a treatment planning framework that accounts for weekly lung tumor shrinkage usi...
BACKGROUND: Induction chemotherapy (ICT) plus concurrent chemoradiotherapy (CCRT) and CCRT alone wer...
Individualized patient profiling is instrumental for personalized management in hepatocellular carc...
Every year cervical cancer affects more than 300,000 people, and on average one woman is diagnosed w...
The aim of the study was to use a previously proposed mask region-based convolutional neural network...
BACKGROUND: A plethora of prognostic biomarkers for esophageal squamous cell carcinoma (ESCC) that h...
PURPOSE: We evaluated the performance of deep learning classifiers for bone scans of prostate cancer...
We are developing imaging methods for a co-clinical trial investigating synergy between immunotherap...
Lung cancer is one of the deadliest forms of cancers and is often diagnosed by performing biopsies w...
Developing deep learning models to analyze histology images has been computationally challenging, as...
BACKGROUND: This study aimed to assess the utility of deep learning analysis using pretreatment FDG-...
With a variety of tumor subtypes, personalized treatments need to identify the subtype of a tumor as...
When doctors use contrast-enhanced computed tomography (CECT) images to predict the metastasis of ax...
For an emerging disease like COVID-19, systems immunology tools may quickly identify and quantitativ...
This article explores the value of wall F-FDG PET/Cr imaging in the diagnosis of thyroid cancer, stu...
INTRODUCTION: This study aims to construct a real-time deep convolutional neural networks (DCNNs) sy...
To compare the surgical outcomes of robot-assisted partial nephrectomy (RAPN) between patients with ...