Oncology/Hematology

Lung Cancer

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

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Decision tree-based machine learning algorithm for prediction of acute radiation esophagitis.

BACKGROUND: Radiation-induced esophagitis remains a significant challenge in thoracic and neck cance...

Deep Learning-Based Auto-Segmentation for Liver Yttrium-90 Selective Internal Radiation Therapy.

The aim was to evaluate a deep learning-based auto-segmentation method for liver delineation in Y-90...

Control of dental calculus Prevents severe Radiation-Induced oral mucositis in patients undergoing radiotherapy for nasopharyngeal carcinoma.

PURPOSE: This study aims to develop an artificial intelligence model to predict severe radiation-ind...

The Role of Eosinophils, Eosinophil-Related Cytokines and AI in Predicting Immunotherapy Efficacy in NSCLC Cancer.

Immunotherapy and chemoimmunotherapy are standard treatments for non-oncogene-addicted advanced non-...

Preoperative Prediction of STAS Risk in Primary Lung Adenocarcinoma Using Machine Learning: An Interpretable Model with SHAP Analysis.

BACKGROUND: Accurate preoperative prediction of spread through air spaces (STAS) in primary lung ade...

Optimizing imaging modalities for sarcoma subtypes in radiation therapy: State of the art.

The choice of imaging modalities is essential in sarcoma management, as different techniques provide...

Precision Oncology in Non-small Cell Lung Cancer: A Comparative Study of Contextualized ChatGPT Models.

OBJECTIVES: The growing adoption of Large Language Models (LLMs) in medicine has raised important qu...

A tumor-infiltrating B lymphocytes -related index based on machine-learning predicts prognosis and immunotherapy response in lung adenocarcinoma.

INTRODUCTION: Tumor-infiltrating B lymphocytes (TILBs) play a pivotal role in shaping the immune mic...

Automated classification of tertiary lymphoid structures in colorectal cancer using TLS-PAT artificial intelligence tool.

Colorectal cancer (CRC) ranks as the third most common and second deadliest cancer worldwide. The im...

Nanomaterial-Based Molecular Imaging in Cancer: Advances in Simulation and AI Integration.

Nanomaterials represent an innovation in cancer imaging by offering enhanced contrast, improved targ...

American College of Veterinary Radiology and European College of Veterinary Diagnostic Imaging position statement on artificial intelligence.

The American College of Veterinary Radiology (ACVR) and the European College of Veterinary Diagnosti...

Stroma and lymphocytes identified by deep learning are independent predictors for survival in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers known to humans. However, ...

A semi-supervised convolutional neural network for diagnosis of pancreatic ductal adenocarcinoma based on EUS-FNA cytological images.

BACKGROUND: The cytological diagnostic process of EUS-FNA smears is time-consuming and manpower-inte...

DPI-MoCo: Deep Prior Image Constrained Motion Compensation Reconstruction for 4D CBCT.

4D cone-beam computed tomography (CBCT) plays a critical role in adaptive radiation therapy for lung...

A multimodal framework for assessing the link between pathomics, transcriptomics, and pancreatic cancer mutations.

In Pancreatic Ductal Adenocarcinoma (PDAC), predicting genetic mutations directly from histopatholog...

Machine learning prediction of overall survival in prostate adenocarcinoma using ensemble techniques.

Prostate adenocarcinoma (PAC) is a complex and common cancer in males and is one of the leading caus...

Robust vs. Non-robust radiomic features: the quest for optimal machine learning models using phantom and clinical studies.

PURPOSE: This study aimed to select robust features against lung motion in a phantom study and use t...

Low-dose CT reconstruction using cross-domain deep learning with domain transfer module.

. X-ray computed tomography employing low-dose x-ray source is actively researched to reduce radiati...

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