Oncology/Hematology

Lung Cancer

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

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Risk factors and socio-economic burden in pancreatic ductal adenocarcinoma operation: a machine learning based analysis.

BACKGROUND: Surgical resection is the major way to cure pancreatic ductal adenocarcinoma (PDAC). How...

Predicting spatial esophageal changes in a multimodal longitudinal imaging study via a convolutional recurrent neural network.

Acute esophagitis (AE) occurs among a significant number of patients with locally advanced lung canc...

Artificial intelligence in image reconstruction: The change is here.

Innovations in CT have been impressive among imaging and medical technologies in both the hardware a...

Renal function in children infected with : a case-control study of an endemic Ghanaian community.

Schistosomiasis has been associated with kidney diseases leading to serious health problems especial...

Improving Image Quality and Reducing Radiation Dose for Pediatric CT by Using Deep Learning Reconstruction.

Background CT deep learning reconstruction (DLR) algorithms have been developed to remove image nois...

Dose-dependent effects of ultrasound therapy on hepatocellular carcinoma.

Non-invasive ischemic cancer therapy requires reduced blood flow whereas drug delivery and radiation...

Using Auto-Segmentation to Reduce Contouring and Dose Inconsistency in Clinical Trials: The Simulated Impact on RTOG 0617.

PURPOSE: Contouring inconsistencies are known but understudied in clinical radiation therapy trials....

Automatic Segmentation Using Deep Learning to Enable Online Dose Optimization During Adaptive Radiation Therapy of Cervical Cancer.

PURPOSE: This study investigated deep learning models for automatic segmentation to support the deve...

Radiomic Detection of EGFR Mutations in NSCLC.

Radiomics is defined as the use of automated or semi-automated post-processing and analysis of multi...

Obtaining PET/CT images from non-attenuation corrected PET images in a single PET system using Wasserstein generative adversarial networks.

Positron emission tomography (PET) imaging plays an indispensable role in early disease detection an...

Dose prediction with deep learning for prostate cancer radiation therapy: Model adaptation to different treatment planning practices.

PURPOSE: This work aims to study the generalizability of a pre-developed deep learning (DL) dose pre...

Non-invasive decision support for NSCLC treatment using PET/CT radiomics.

Two major treatment strategies employed in non-small cell lung cancer, NSCLC, are tyrosine kinase in...

Artificial Intelligence and Its Role in Identifying Esophageal Neoplasia.

Randomized trials have demonstrated that ablation of dysplastic Barrett's esophagus can reduce the r...

Feasibility, safety and efficacy of argon beam coagulation in robot-assisted partial nephrectomy for solid renal masses ≤ 7 cm in size.

One of the most important steps of the partial nephrectomy (PN) is hemostatic control of tumor bed w...

The Coming of Age for Big Data in Systems Radiobiology, an Engineering Perspective.

As high-throughput approaches in biological and biomedical research are transforming the life scienc...

Integration of AI and Machine Learning in Radiotherapy QA.

The use of machine learning and other sophisticated models to aid in prediction and decision making ...

Clinical evaluation of atlas- and deep learning-based automatic segmentation of multiple organs and clinical target volumes for breast cancer.

Manual segmentation is the gold standard method for radiation therapy planning; however, it is time-...

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