Oncology/Hematology

Lung Cancer

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

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Deciphering the fibrotic process: mechanism of chronic radiation skin injury fibrosis.

This review explores the mechanisms of chronic radiation-induced skin injury fibrosis, focusing on t...

METnet: A novel deep learning model predicting MET dysregulation in non-small-cell lung cancer on computed tomography images.

BACKGROUND: Mesenchymal epithelial transformation (MET) is a key molecular target for diagnosis and ...

Single-Port Multiport Robot-Assisted Partial Nephrectomy: A Meta-Analysis.

Several centers have reported their experience with single-port robot-assisted partial nephrectomy ...

Identifying Pathological Subtypes of Brain Metastasis from Lung Cancer Using MRI-Based Deep Learning Approach: A Multicenter Study.

The aim of this study was to investigate the feasibility of deep learning (DL) based on multiparamet...

Effect of Febuxostat versus Allopurinol on the Glomerular Filtration Rate and Hyperuricemia in Patients with Chronic Kidney Disease.

Hyperuricemia is a risk factor for the progression of chronic kidney disease (CKD). We compared febu...

[Not Available].

BACKGROUND:: Efficient and accurate delineation of organs at risk (OARs) is a critical procedure for...

Deep learning-based algorithms for low-dose CT imaging: A review.

The computed tomography (CT) technique is extensively employed as an imaging modality in clinical se...

Machine learning based on blood test biomarkers predicts fast progression in advanced NSCLC patients treated with immunotherapy.

OBJECTIVE: Fast progression (FP) represents a desperate situation for advanced non-small cell lung c...

Edge roughness quantifies impact of physician variation on training and performance of deep learning auto-segmentation models for the esophagus.

Manual segmentation of tumors and organs-at-risk (OAR) in 3D imaging for radiation-therapy planning ...

GlioPredictor: a deep learning model for identification of high-risk adult IDH-mutant glioma towards adjuvant treatment planning.

Identification of isocitrate dehydrogenase (IDH)-mutant glioma patients at high risk of early progre...

Clinical assessment of deep learning-based uncertainty maps in lung cancer segmentation.

. Prior to radiation therapy planning, accurate delineation of gross tumour volume (GTVs) and organs...

DARDN: A Deep-Learning Approach for CTCF Binding Sequence Classification and Oncogenic Regulatory Feature Discovery.

Characterization of gene regulatory mechanisms in cancer is a key task in cancer genomics. CCCTC-bin...

Deep Learning Auto-Segmentation Network for Pediatric Computed Tomography Data Sets: Can We Extrapolate From Adults?

PURPOSE: Artificial intelligence (AI)-based auto-segmentation models hold promise for enhanced effic...

CT image denoising methods for image quality improvement and radiation dose reduction.

With the ever-increasing use of computed tomography (CT), concerns about its radiation dose have bec...

Explainable deep learning-based survival prediction for non-small cell lung cancer patients undergoing radical radiotherapy.

BACKGROUND AND PURPOSE: Survival is frequently assessed using Cox proportional hazards (CPH) regress...

Hyperpolarized Gas Imaging in Lung Diseases: Functional and Artificial Intelligence Perspective.

Pathophysiologic changes in lung diseases are often accompanied by changes in ventilation and gas ex...

Exposure-response analysis using time-to-event data for bevacizumab biosimilar SB8 and the reference bevacizumab.

This analysis aimed to characterize the exposure-response relationship of bevacizumab in non-small-...

Computer-aided diagnosis of distal metastasis in non-small cell lung cancer by low-dose CT based radiomics and deep learning signatures.

BACKGROUND: This study aimed to develop and validate radiomics and deep learning (DL) signatures for...

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