AIMC Topic: Lung Neoplasms

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

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Sep 14, 2021
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 ...
Spectrum Analysis, Raman Adenocarcinoma Adenocarcinoma of Lung Carcinoma, Squamous Cell Deep Learning Lung Neoplasms Humans
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A Hybrid Method to Predict Postoperative Survival of Lung Cancer Using Improved SMOTE and Adaptive SVM.

Computational and mathematical methods in medicine Sep 10, 2021
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...
Fuzzy Logic Lung Neoplasms Humans Computational Biology Algorithms Survival Analysis Support Vector Machine Databases, Factual Computer Heuristics
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Selection, Visualization, and Interpretation of Deep Features in Lung Adenocarcinoma and Squamous Cell Carcinoma.

The American journal of pathology Sep 8, 2021
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...
Diagnosis, Differential Feasibility Studies Image Interpretation, Computer-Assisted Deep Learning Image Processing, Computer-Assisted Lung Neoplasms Datasets as Topic Adenocarcinoma of Lung Sensitivity and Specificity Male Carcinoma, Squamous Cell Humans Reproducibility of Results Neural Networks, Computer Female
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Analysis of the short-term outcomes of biportal robot-assisted lobectomy.

The international journal of medical robotics + computer assisted surgery : MRCAS Sep 2, 2021
BACKGROUND: The present study aimed to assess the short-term consequences of biportal robot-assisted lobectomy, validating its safety and effectiveness.
Pneumonectomy Thoracic Surgery, Video-Assisted Lung Neoplasms Lymph Node Excision Humans Robotics Retrospective Studies Male Aged Female Middle Aged Adult
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Combining computed tomography and biologically effective dose in radiomics and deep learning improves prediction of tumor response to robotic lung stereotactic body radiation therapy.

Medical physics Sep 2, 2021
PURPOSE: The aim of this study is to improve the performance of machine learning (ML) models in predicting response of non-small cell lung cancer (NSCLC) to stereotactic body radiation therapy (SBRT) by integrating image features from pre-treatment c...
Humans Lung Neoplasms Carcinoma, Non-Small-Cell Lung Robotic Surgical Procedures Radiosurgery Tomography, X-Ray Computed Lung Deep Learning
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Quantitative analysis of metastatic breast cancer in mice using deep learning on cryo-image data.

Scientific reports Sep 1, 2021
Cryo-imaging sections and images a whole mouse and provides ~ 120-GBytes of microscopic 3D color anatomy and fluorescence images, making fully manual analysis of metastases an onerous task. A convolutional neural network (CNN)-based metastases segmen...
Female Brain Neoplasms Animals Deep Learning Neural Networks, Computer Mice Bone Neoplasms Liver Neoplasms Mammary Neoplasms, Experimental Image Processing, Computer-Assisted Lung Neoplasms
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Domain Adaptation-Based Deep Learning for Automated Tumor Cell (TC) Scoring and Survival Analysis on PD-L1 Stained Tissue Images.

IEEE transactions on medical imaging Aug 31, 2021
We report the ability of two deep learning-based decision systems to stratify non-small cell lung cancer (NSCLC) patients treated with checkpoint inhibitor therapy into two distinct survival groups. Both systems analyze functional and morphological p...
Deep Learning Lung Neoplasms B7-H1 Antigen Humans Immunohistochemistry Carcinoma, Non-Small-Cell Lung Biomarkers, Tumor Survival Analysis
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Machine Learning-Based Radiomics Signatures for EGFR and KRAS Mutations Prediction in Non-Small-Cell Lung Cancer.

International journal of molecular sciences Aug 26, 2021
Early identification of epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations is crucial for selecting a therapeutic strategy for patients with non-small-cell lung cancer (NSCLC). We proposed a machin...
ErbB Receptors Aged Proto-Oncogene Proteins p21(ras) Aged, 80 and over Algorithms Male Biomarkers Tomography, X-Ray Computed Carcinoma, Non-Small-Cell Lung Humans Middle Aged Mutation Female Neoplasm Staging Machine Learning ROC Curve Supervised Machine Learning Lung Neoplasms Reproducibility of Results
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A survey of computer-aided diagnosis of lung nodules from CT scans using deep learning.

Computers in biology and medicine Aug 25, 2021
Lung cancer has one of the highest mortalities of all cancers. According to the National Lung Screening Trial, patients who underwent low-dose computed tomography (CT) scanning once a year for 3 years showed a 20% decline in lung cancer mortality. To...
Lung Deep Learning Lung Neoplasms Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Computers Tomography, X-Ray Computed Sensitivity and Specificity Humans
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A deep learning-based dual-omics prediction model for radiation pneumonitis.

Medical physics Aug 25, 2021
PURPOSE: Radiation pneumonitis (RP) is the main source of toxicity in thoracic radiotherapy. This study proposed a deep learning-based dual-omics model, which aims to improve the RP prediction performance by integrating more data points and exploring...
Humans Four-Dimensional Computed Tomography Deep Learning Lung Neoplasms Carcinoma, Non-Small-Cell Lung Radiation Pneumonitis
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