AIMC Topic: Lung Neoplasms
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: deep learning-based radiomics for the time-to-event outcome prediction in lung cancer.
Scientific reports
Jul 23, 2020
Hand-crafted radiomics has been used for developing models in order to predict time-to-event clinical outcomes in patients with lung cancer. Hand-crafted features, however, are pre-defined and extracted without taking the desired target into account....
Discrimination between transient and persistent subsolid pulmonary nodules on baseline CT using deep transfer learning.
European radiology
Jul 21, 2020
OBJECTIVES: To develop and validate a deep learning model to discriminate transient from persistent subsolid nodules (SSNs) on baseline CT.
Deep Learning-based Automatic Detection Algorithm for Reducing Overlooked Lung Cancers on Chest Radiographs.
Radiology
Jul 21, 2020
Background It is uncertain whether a deep learning-based automatic detection algorithm (DLAD) for identifying malignant nodules on chest radiographs will help diagnose lung cancers. Purpose To evaluate the efficacy of using a DLAD in observer perform...
Machine learning of serum metabolic patterns encodes early-stage lung adenocarcinoma.
Nature communications
Jul 16, 2020
Early cancer detection greatly increases the chances for successful treatment, but available diagnostics for some tumours, including lung adenocarcinoma (LA), are limited. An ideal early-stage diagnosis of LA for large-scale clinical use must address...
[Technological Innovations in Pulmonology - Examples from Diagnostics and Therapy].
Pneumologie (Stuttgart, Germany)
Jul 14, 2020
A significant proportion of the current technological developments in pneumology originate from the various areas of information technology. The spectrum ranges from smartphone apps to be used in daily life or in patient care to the use of artificial...
Histological Subtypes Classification of Lung Cancers on CT Images Using 3D Deep Learning and Radiomics.
Academic radiology
Jul 1, 2020
RATIONALE AND OBJECTIVES: Histological subtypes of lung cancers are critical for clinical treatment decision. In this study, we attempt to use 3D deep learning and radiomics methods to automatically distinguish lung adenocarcinomas (ADC), squamous ce...
Intraoperative complications and troubles in robot-assisted anatomical pulmonary resection.
General thoracic and cardiovascular surgery
Jul 1, 2020
OBJECTIVE: Regarding intraoperative complications and troubles during robot-assisted thoracic surgery, few data are available especially in Japan. This study was aimed to elucidate intraoperative complications and troubles in robotic anatomical lung ...
The major effects of health-related quality of life on 5-year survival prediction among lung cancer survivors: applications of machine learning.
Scientific reports
Jul 1, 2020
The primary goal of this study was to evaluate the major roles of health-related quality of life (HRQOL) in a 5-year lung cancer survival prediction model using machine learning techniques (MLTs). The predictive performances of the models were compar...
Solitary solid pulmonary nodules: a CT-based deep learning nomogram helps differentiate tuberculosis granulomas from lung adenocarcinomas.
European radiology
Jun 27, 2020
OBJECTIVES: To evaluate the differential diagnostic performance of a computed tomography (CT)-based deep learning nomogram (DLN) in identifying tuberculous granuloma (TBG) and lung adenocarcinoma (LAC) presenting as solitary solid pulmonary nodules (...
Pattern Recognition, Automated
Tomography, X-Ray Computed
Calibration
Female
Adenocarcinoma of Lung
Tuberculosis
Image Processing, Computer-Assisted
Adult
Humans
Sex Factors
Lung Neoplasms
Male
Algorithms
Solitary Pulmonary Nodule
Diagnostic Tests, Routine
Logistic Models
Retrospective Studies
Observer Variation
Middle Aged
Regression Analysis
Nomograms
Diagnosis, Computer-Assisted
Age Factors
Diagnosis, Differential
Deep Learning
Granuloma
ROC Curve
An Artificial Intelligence Model for Predicting 1-Year Survival of Bone Metastases in Non-Small-Cell Lung Cancer Patients Based on XGBoost Algorithm.
BioMed research international
Jun 27, 2020
Non-small-cell lung cancer (NSCLC) patients often develop bone metastases (BM), and the overall survival for these patients is usually perishing. However, a model with high accuracy for predicting the survival of NSCLC with BM is still lacking. Here,...
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