AIMC Topic: Lung Neoplasms

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[Robot-assisted thoracic surgery-Areas of application and limitations].

Der Chirurg; Zeitschrift fur alle Gebiete der operativen Medizen Feb 1, 2021
The proportion of robot-assisted thoracic surgery (RATS) is continuously increasing. The main areas of clinical application are anatomical lung resections with lymphadenectomy and resection of mediastinal tumors. Especially in the area of the thymus ...
Thoracic Surgery Robotics Robotic Surgical Procedures Thoracic Surgery, Video-Assisted Humans Lung Neoplasms Lymph Node Excision
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Can a Novel Deep Neural Network Improve the Computer-Aided Detection of Solid Pulmonary Nodules and the Rate of False-Positive Findings in Comparison to an Established Machine Learning Computer-Aided Detection?

Investigative radiology Feb 1, 2021
OBJECTIVE: The aim of this study was to compare the performance of 2 approved computer-aided detection (CAD) systems for detection of pulmonary solid nodules (PSNs) in an oncologic cohort. The first CAD system is based on a conventional machine learn...
Humans Neural Networks, Computer Sensitivity and Specificity Lung Neoplasms Machine Learning Radiographic Image Interpretation, Computer-Assisted Computers Retrospective Studies
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Predictors of Survival among Male and Female Patients with Malignant Pleural Mesothelioma: A Random Survival Forest Analysis of Data from the 2000-2017 Surveillance, Epidemiology, and End Results Program.

Journal of registry management Jan 1, 2021
BACKGROUND: Malignant pleural mesothelioma (MPM) is a rare and aggressive malignancy with a dismal prognosis. We aimed to identify predictors of survival among male and female MPM patients in the United States.
Lung Neoplasms Mesothelioma Female Mesothelioma, Malignant Pleural Neoplasms Humans Survival Rate SEER Program Prognosis Male
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Differentiating Small-Cell Lung Cancer From Non-Small-Cell Lung Cancer Brain Metastases Based on MRI Using Efficientnet and Transfer Learning Approach.

Technology in cancer research & treatment Jan 1, 2021
Differentiation between small-cell lung cancer (SCLC) from non-small-cell lung cancer (NSCLC) brain metastases is crucial due to the different clinical behaviors of the two tumor types. We propose the use of a deep learning and transfer learning appr...
Female Brain Neoplasms Male Middle Aged ROC Curve Lung Neoplasms Machine Learning Diagnosis, Differential Humans Prognosis Image Interpretation, Computer-Assisted Carcinoma, Non-Small-Cell Lung Retrospective Studies Small Cell Lung Carcinoma Follow-Up Studies Magnetic Resonance Imaging
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Prediction of Radiation Pneumonitis With Machine Learning in Stage III Lung Cancer: A Pilot Study.

Technology in cancer research & treatment Jan 1, 2021
BACKGROUND: Radiation pneumonitis (RP) is a dose-limiting toxicity in lung cancer radiotherapy (RT). As risk factors in the development of RP, patient and tumor characteristics, dosimetric parameters, and treatment features are intertwined, and it is...
Radiotherapy Radiation Pneumonitis Middle Aged Pilot Projects ROC Curve Lung Neoplasms Follow-Up Studies Bayes Theorem Aged, 80 and over Adult Male Humans Risk Factors Neural Networks, Computer Aged Machine Learning Algorithms Prognosis Female
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Detection of Lung Cancer on Computed Tomography Using Artificial Intelligence Applications Developed by Deep Learning Methods and the Contribution of Deep Learning to the Classification of Lung Carcinoma.

Current medical imaging Jan 1, 2021
BACKGROUND: Every year, lung cancer contributes to a high percentage deaths in the world. Early detection of lung cancer is important for its effective treatment, and non-invasive rapid methods are usually used for diagnosis.
Artificial Intelligence Tomography, X-Ray Computed Carcinoma, Squamous Cell Humans Lung Deep Learning Lung Neoplasms
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Lung Nodule Detection using Convolutional Neural Networks with Transfer Learning on CT Images.

Combinatorial chemistry & high throughput screening Jan 1, 2021
AIM AND OBJECTIVE: Lung nodule detection is critical in improving the five-year survival rate and reducing mortality for patients with lung cancer. Numerous methods based on Convolutional Neural Networks (CNNs) have been proposed for lung nodule dete...
Humans Neural Networks, Computer Machine Learning Tomography, X-Ray Computed Lung Neoplasms
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The Regimen of Computed Tomography Screening for Lung Cancer: Lessons Learned Over 25 Years From the International Early Lung Cancer Action Program.

Journal of thoracic imaging Jan 1, 2021
We learned many unanticipated and valuable lessons since we started planning our study of low-dose computed tomography (CT) screening for lung cancer in 1991. The publication of the baseline results of the Early Lung Cancer Action Project (ELCAP) in ...
Lung Neoplasms Mass Screening Early Detection of Cancer Humans Artificial Intelligence Tomography, X-Ray Computed
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[Pathological diagnosis of lung cancer based on deep transfer learning].

Zhonghua bing li xue za zhi = Chinese journal of pathology Nov 8, 2020
To establish an artificial intelligence (AI)-assisted diagnostic system for lung cancer via deep transfer learning. The researchers collected 519 lung pathologic slides from 2016 to 2019, covering various lung tissues, including normal tissues, ade...
Lung Neoplasms Artificial Intelligence Databases, Factual Deep Learning Humans Neural Networks, Computer
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Artificial intelligence is improving the detection of lung cancer.

Nature Nov 1, 2020
Lung Neoplasms Humans Mass Screening Artificial Intelligence Databases as Topic Early Detection of Cancer Clinical Decision-Making Deep Learning
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