AIMC Topic: Lung Neoplasms

Clear Filters Showing 951 to 960 of 1778 articles

Deep Learning-Based Computed Tomography Imaging to Diagnose the Lung Nodule and Treatment Effect of Radiofrequency Ablation.

Journal of healthcare engineering
This study aimed to detect and diagnose the lung nodules as early as possible to effectively treat them, thereby reducing the burden on the medical system and patients. A lung computed tomography (CT) image segmentation algorithm was constructed base...

Adaptive Diagnosis of Lung Cancer by Deep Learning Classification Using Wilcoxon Gain and Generator.

Journal of healthcare engineering
Cancer is a complicated worldwide health issue with an increasing death rate in recent years. With the swift blooming of the high throughput technology and several machine learning methods that have unfolded in recent years, progress in cancer diseas...

3D multi-scale, multi-task, and multi-label deep learning for prediction of lymph node metastasis in T1 lung adenocarcinoma patients' CT images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The diagnosis of preoperative lymph node (LN) metastasis is crucial to evaluate possible therapy options for T1 lung adenocarcinoma patients. Radiologists preoperatively diagnose LN metastasis by evaluating signs related to LN metastasis, like spicul...

New Technique for Introducing a Surgical Stapler during Robot-Assisted Lobectomy for Lung Cancer.

Journal of Nippon Medical School = Nippon Ika Daigaku zasshi
BACKGROUND: The da Vinci Si version robot lacks a vascular stapler that can be controlled by the operating surgeon at the surgical console when dividing pulmonary vessels. Therefore, to initiate and safely perform robotic anatomical lobectomy for lun...

An [18F]FDG-PET/CT deep learning method for fully automated detection of pathological mediastinal lymph nodes in lung cancer patients.

European journal of nuclear medicine and molecular imaging
PURPOSE: The identification of pathological mediastinal lymph nodes is an important step in the staging of lung cancer, with the presence of metastases significantly affecting survival rates. Nodes are currently identified by a physician, but this pr...

Highly accurate diagnosis of lung adenocarcinoma and squamous cell carcinoma tissues by deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Intraoperative detection of the marginal tissues is the last and most important step to complete the resection of adenocarcinoma and squamous cell carcinoma. However, the current intraoperative diagnosis is time-consuming and requires numerous steps ...

A Hybrid Method to Predict Postoperative Survival of Lung Cancer Using Improved SMOTE and Adaptive SVM.

Computational and mathematical methods in medicine
Predicting postoperative survival of lung cancer patients (LCPs) is an important problem of medical decision-making. However, the imbalanced distribution of patient survival in the dataset increases the difficulty of prediction. Although the syntheti...

Selection, Visualization, and Interpretation of Deep Features in Lung Adenocarcinoma and Squamous Cell Carcinoma.

The American journal of pathology
Although deep learning networks applied to digital images have shown impressive results for many pathology-related tasks, their black-box approach and limitation in terms of interpretability are significant obstacles for their widespread clinical uti...