Lung Cancer

Dual residual convolutional neural network (DRCNN) for low-dose CT imaging.

The excessive radiation doses in the application of computed tomography (CT) technology pose a threat to the health of patients. However, applying a low radiation dose in CT can result in severe artifacts and noise in the captured images, thus affecting the diagnosis. Therefore, in this study, we investigate a dual residual convolution neural network (DRCNN) for low-dose CT (LDCT) imaging, whereby...

In-Cell Single-Molecule Analysis of Molecular State and Reaction Kinetics Coupling.

Cellular signaling is regulated by the spatiotemporal dynamics and kinetics of molecular behavior. To investigate the mechanisms at the molecular level, fluorescence single-molecule analysis is an effective method owing to the direct observation of individual molecules in situ in cells and the results in quantitative information about the behavior. The integration of machine learning into this ana...

Prediction of Radiation Pneumonitis With Machine Learning in Stage III Lung Cancer: A Pilot Study.

BACKGROUND: Radiation pneumonitis (RP) is a dose-limiting toxicity in lung cancer radiotherapy (RT). As risk factors in the development of RP, patient...

Differentiating Small-Cell Lung Cancer From Non-Small-Cell Lung Cancer Brain Metastases Based on MRI Using Efficientnet and Transfer Learning Approach.

Differentiation between small-cell lung cancer (SCLC) from non-small-cell lung cancer (NSCLC) brain metastases is crucial due to the different clinica...

The Application and Development of Deep Learning in Radiotherapy: A Systematic Review.

With the massive use of computers, the growth and explosion of data has greatly promoted the development of artificial intelligence (AI). The rise of ...

[A Study on Radiation Dermatitis Grading Support System Based on Deep Learning by Hybrid Generation Method].

PURPOSE: Radiation dermatitis is one of the most common adverse events in patients undergoing radiotherapy. However, the objective evaluation of this ...

[Automation of Damage Detection and Damage Area Measurement of X-ray Protective Clothing Using Deep Learning].

PURPOSE: Damage to shielding sheets on X-ray protective clothing may be a cause of increased radiation exposure. To prevent increased radiation exposu...

Prognosticating Outcome in Pancreatic Head Cancer With the use of a Machine Learning Algorithm.

The purpose of this project is to identify prognostic features in resectable pancreatic head adenocarcinoma and use these features to develop a machi...

Robotic surgical staging of lymphadenectomy during pregnancy - case report.

OBJECTIVE: We aim to present a case of a 43-year-old patient dia-gnosed with cervical adenocarcinoma in the 15th week of pregnancy, who underwent robo...

Effect of Ramadan Fasting on Chronic Inflammation and Body Composition in Patients with Chronic Kidney Disease.

Chronic kidney disease (CKD) is associated with a state of chronic inflammation which is responsible for many of the pathophysiological changes detect...

Chronic kidney disease in Hepatitis C and its association with liver cirrhosis and viral load: Revealing the importance of hematuria.

Hepatitis C virus (HCV) contributed as a risk factor for chronic kidney disease (CKD). Many studies only showed it associated with estimated glomerula...

The Role of Chronic Renal Disease on the Linking Obesity/Hypertension.

Obesity is accompanied by several disorders. This study investigated the role of chronic renal disease on the linking obesity/hypertension (HTN). It a...

Determination of Serum Perfluorooctanoic Acid and Perfluorooctanesulfonic Acid Levels with Different Stages of Chronic Kidney Disease.

The aim of this study is to investigate the perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) levels in patients with different st...

Clinical Presentation, Histology, and Outcomes of Immunoglobulin A Nephropathy: A Single-Center Experience from Pakistan.

Clinical presentation, kidney biopsy findings, and clinical outcomes of immunoglobulin A nephropathy (IgAN) are highly variable. The objective of this...

[Pathological diagnosis of lung cancer based on deep transfer learning].

To establish an artificial intelligence (AI)-assisted diagnostic system for lung cancer via deep transfer learning. The researchers collected 519 lu...

TMLRpred: A machine learning classification model to distinguish reversible EGFR double mutant inhibitors.

The EGFR is a clinically important therapeutic drug target in lung cancer. The first-generation tyrosine kinase inhibitors used in clinics are effecti...

A fatal invasive pulmonary infection in an adult patient with malignant lung adenocarcinoma.

BACKGROUND AND PURPOSE: complex as a ubiquitous environmental mold is increasingly reported to cause an invasive fungal infection in immunosuppressiv...

Comparison between atlas and convolutional neural network based automatic segmentation of multiple organs at risk in non-small cell lung cancer.

Delineation of organs at risk (OARs) is important but time consuming for radiotherapy planning. Automatic segmentation of OARs based on convolutional ...

Next-Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Algorithms.

PURPOSE: Considerable progress has been made in the assessment and management of non-small cell lung cancer (NSCLC) patients based on mutation status ...

Omitting Cortical Renorrhaphy in Robot-Assisted Partial Nephrectomy: Is it Safe? A Single Center Large Case Series.

Preserving renal function after robot-assisted partial nephrectomy (RAPN) is important and influenced by the technique of renal reconstruction among ...