Lung Cancer

Deep cross-modality (MR-CT) educed distillation learning for cone beam CT lung tumor segmentation.

PURPOSE: Despite the widespread availability of in-treatment room cone beam computed tomography (CBC...

Moving Forward in the Next Decade: Radiation Oncology Sciences for Patient-Centered Cancer Care.

In a time of rapid advances in science and technology, the opportunities for radiation oncology are ...

Deep-learning-based image registration and automatic segmentation of organs-at-risk in cone-beam CT scans from high-dose radiation treatment of pancreatic cancer.

PURPOSE: Accurate deformable registration between computed tomography (CT) and cone-beam CT (CBCT) i...

Greater Renal Function Benefit from Enucleation Technique for More Complex Renal Tumors in Robot-Assisted Partial Nephrectomy.

Tumor enucleation technique in robot-assisted partial nephrectomy (RAPN) reportedly contributes to ...

Metrics to evaluate the performance of auto-segmentation for radiation treatment planning: A critical review.

Advances in artificial intelligence-based methods have led to the development and publication of num...

Integration of machine learning and genome-scale metabolic modeling identifies multi-omics biomarkers for radiation resistance.

Resistance to ionizing radiation, a first-line therapy for many cancers, is a major clinical challen...

Cytotoxicity and cell imaging of six types of carbon nanodots prepared through carbonization and hydrothermal processing of natural plant materials.

In this study we prepared six types of carbon nanodots (CNDs) from natural plant materials - through...

Conjunctival Provocation Test With .

Conjunctival provocation test (CPT) is used to demonstrate clinical relevance to a specific allerge...

A deep learning-based auto-segmentation system for organs-at-risk on whole-body computed tomography images for radiation therapy.

BACKGROUND AND PURPOSE: Delineating organs at risk (OARs) on computed tomography (CT) images is an e...

Providing an accurate global model for monthly solar radiation forecasting using artificial intelligence based on air quality index and meteorological data of different cities worldwide.

This study aims to present an exact model for predicting solar radiation worldwide through a general...

Digital/Computational Technology for Molecular Cytology Testing: A Short Technical Note with Literature Review.

This short article describes the method of digital cytopathology using Z-stack scanning with or with...

Artificial Intelligence-Assisted Amphiregulin and Epiregulin IHC Predicts Panitumumab Benefit in Wild-Type Metastatic Colorectal Cancer.

PURPOSE: High tumor mRNA levels of the EGFR ligands amphiregulin (AREG) and epiregulin (EREG) are as...

Radiomics analysis on CT images for prediction of radiation-induced kidney damage by machine learning models.

INTRODUCTION: We aimed to assess the power of radiomic features based on computed tomography to pred...

A deep learning model to detect pancreatic ductal adenocarcinoma on endoscopic ultrasound-guided fine-needle biopsy.

Histopathological diagnosis of pancreatic ductal adenocarcinoma (PDAC) on endoscopic ultrasonography...

MET Exon 14 Skipping: A Case Study for the Detection of Genetic Variants in Cancer Driver Genes by Deep Learning.

BACKGROUND: Disruption of alternative splicing (AS) is frequently observed in cancer and might repre...

Robotic hepatectomy and biliary reconstruction for perihilar cholangiocarcinoma: a pioneer western case series.

Open surgery is the standard of care for perihilar cholangiocarcinoma (pCCA). With the aim of oncolo...

Deep learning reconstruction of digital breast tomosynthesis images for accurate breast density and patient-specific radiation dose estimation.

The two-dimensional nature of mammography makes estimation of the overall breast density challenging...

Triage-driven diagnosis of Barrett's esophagus for early detection of esophageal adenocarcinoma using deep learning.

Deep learning methods have been shown to achieve excellent performance on diagnostic tasks, but how ...

A deep learning model for the classification of indeterminate lung carcinoma in biopsy whole slide images.

The differentiation between major histological types of lung cancer, such as adenocarcinoma (ADC), s...

10 Commandments of Robotic Lobectomy.

Simulating reference crop evapotranspiration with different climate data inputs using Gaussian exponential model.

Obtaining accurate data on reference crop evapotranspiration (ET) is important for agricultural wate...