Oncology/Hematology

Lung Cancer

Latest AI and machine learning research in lung cancer for healthcare professionals.

8,053 articles
Stay Ahead - Weekly Lung Cancer research updates
Subscribe
Browse Categories
Showing 1450-1470 of 8,053 articles
Outcome of kidney function in adults on long-term home parenteral nutrition for chronic intestinal failure.

OBJECTIVE: The aim of this study was to evaluate kidney function outcome in adults on home parentera...

Temporal separation of Cerenkov radiation and scintillation using artificial neural networks in Clinical LINACs.

The irradiation of scintillator-fiber optic dosimeters by clinical LINACs results in the measurement...

STRAINet: Spatially Varying sTochastic Residual AdversarIal Networks for MRI Pelvic Organ Segmentation.

Accurate segmentation of pelvic organs is important for prostate radiation therapy. Modern radiation...

3-D Quantification of Filopodia in Motile Cancer Cells.

We present a 3D bioimage analysis workflow to quantitatively analyze single, actin-stained cells wit...

Effect of machine learning methods on predicting NSCLC overall survival time based on Radiomics analysis.

BACKGROUND: To investigate the effect of machine learning methods on predicting the Overall Survival...

An Increased Level of Aryl Hydrocarbon Receptor in Patients with Pancreatic Cancer.

BACKGROUND Aryl-carbon receptor (AhR), a ligand-activated transcription factor, is best known for it...

3D Deep Learning from CT Scans Predicts Tumor Invasiveness of Subcentimeter Pulmonary Adenocarcinomas.

: Identification of early-stage pulmonary adenocarcinomas before surgery, especially in cases of sub...

A dynamic model for predicting graft function in kidney recipients' upcoming follow up visits: A clinical application of artificial neural network.

BACKGROUND: Predicting the function of transplanted kidneys would help clinicians in individualized ...

Development of deep neural network for individualized hepatobiliary toxicity prediction after liver SBRT.

BACKGROUND: Accurate prediction of radiation toxicity of healthy organs-at-risks (OARs) critically d...

Classification of lung adenocarcinoma transcriptome subtypes from pathological images using deep convolutional networks.

PURPOSE: Convolutional neural networks have become rapidly popular for image recognition and image a...

Machine learning and modeling: Data, validation, communication challenges.

With the era of big data, the utilization of machine learning algorithms in radiation oncology is ra...

The radiation oncology ontology (ROO): Publishing linked data in radiation oncology using semantic web and ontology techniques.

PURPOSE: Personalized medicine is expected to yield improved health outcomes. Data mining over massi...

RASPELD to Perform High-End Screening in an Academic Environment toward the Development of Cancer Therapeutics.

The identification of compounds for dissecting biological functions and the development of novel dru...

Diagnostic outcomes of esophageal cancer by artificial intelligence using convolutional neural networks.

BACKGROUND AND AIMS: The prognosis of esophageal cancer is relatively poor. Patients are usually dia...

Knowledge-Based Planning for Identifying High-Risk Stereotactic Ablative Radiation Therapy Treatment Plans for Lung Tumors Larger Than 5 cm.

PURPOSE: Stereotactic ablative body radiation therapy (SABR) for lung tumors ≥5 cm can be associated...

Identifying epidermal growth factor receptor mutation status in patients with lung adenocarcinoma by three-dimensional convolutional neural networks.

OBJECTIVE:: Genetic phenotype plays a central role in making treatment decisions of lung adenocarcin...

Browse Categories