AIMC Topic: Lung Neoplasms

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Sybil: A Validated Deep Learning Model to Predict Future Lung Cancer Risk From a Single Low-Dose Chest Computed Tomography.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology Jan 12, 2023
PURPOSE: Low-dose computed tomography (LDCT) for lung cancer screening is effective, although most eligible people are not being screened. Tools that provide personalized future cancer risk assessment could focus approaches toward those most likely t...
Mass Screening Early Detection of Cancer Tomography, X-Ray Computed Lung Humans Deep Learning Lung Neoplasms
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Predicting N2 lymph node metastasis in presurgical stage I-II non-small cell lung cancer using multiview radiomics and deep learning method.

Medical physics Jan 6, 2023
BACKGROUND: Accurate diagnosis of N2 lymph node status of the resectable stage I-II non-small cell lung cancer (NSCLC) before surgery is crucial, while there is lack of corresponding method clinically.
Humans Carcinoma, Non-Small-Cell Lung Retrospective Studies Lymphatic Metastasis Deep Learning Carcinoma Lung Neoplasms
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Feasibility study of deep learning-based markerless real-time lung tumor tracking with orthogonal X-ray projection images.

Journal of applied clinical medical physics Dec 28, 2022
PURPOSE: The feasibility of a deep learning-based markerless real-time tumor tracking (RTTT) method was retrospectively studied with orthogonal kV X-ray images and clinical tracking records acquired during lung cancer treatment.
X-Rays Humans Lung Neoplasms Retrospective Studies Feasibility Studies Deep Learning
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A deep-learning model for transforming the style of tissue images from cryosectioned to formalin-fixed and paraffin-embedded.

Nature biomedical engineering Dec 23, 2022
Histological artefacts in cryosectioned tissue can hinder rapid diagnostic assessments during surgery. Formalin-fixed and paraffin-embedded (FFPE) tissue provides higher quality slides, but the process for obtaining them is laborious (typically lasti...
Carcinoma, Non-Small-Cell Lung Formaldehyde Paraffin Embedding Deep Learning Lung Neoplasms Humans
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Developing Artificial Intelligence Models for Extracting Oncologic Outcomes from Japanese Electronic Health Records.

Advances in therapy Dec 22, 2022
INTRODUCTION: A framework that extracts oncological outcomes from large-scale databases using artificial intelligence (AI) is not well established. Thus, we aimed to develop AI models to extract outcomes in patients with lung cancer using unstructure...
East Asian People Bayes Theorem Electronic Health Records Lung Neoplasms Humans Artificial Intelligence
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A Novel Deep Learning Model Based on Multi-Scale and Multi-View for Detection of Pulmonary Nodules.

Journal of digital imaging Dec 21, 2022
Lung cancer manifests as pulmonary nodules in the early stage. Thus, the early and accurate detection of these nodules is crucial for improving the survival rate of patients. We propose a novel two-stage model for lung nodule detection. In the candid...
Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Lung Neoplasms Multiple Pulmonary Nodules Humans Lung Deep Learning China
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Robot-assisted segmentectomy for small lung cancer using a radiofrequency identification marker.

Asian cardiovascular & thoracic annals Dec 21, 2022
Owing to the prevalence of robot-assisted thoracoscopic surgery and the increase in the number of small lung cancer cases, robot-assisted thoracoscopic segmentectomy cases have also been increasing. For small lung cancers, such as ground-glass opacit...
Robotics Robotic Surgical Procedures Humans Lung Neoplasms Mastectomy, Segmental Pneumonectomy Thoracic Surgery, Video-Assisted
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Diagnostic test accuracy of artificial intelligence-based imaging for lung cancer screening: A systematic review and meta-analysis.

Lung cancer (Amsterdam, Netherlands) Dec 15, 2022
BACKGROUND: Lung cancer is the principal cause of cancer-related deaths worldwide. Early detection of lung cancer with screening is indispensable to reduce the high morbidity and mortality rates. Artificial intelligence (AI) is widely utilised in hea...
Diagnostic Tests, Routine Humans Early Detection of Cancer Artificial Intelligence Diagnostic Imaging Lung Neoplasms
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Deep-Learning Algorithm and Concomitant Biomarker Identification for NSCLC Prediction Using Multi-Omics Data Integration.

Biomolecules Dec 8, 2022
Early diagnosis of lung cancer to increase the survival rate, which is currently at a low range of mid-30%, remains a critical need. Despite this, multi-omics data have rarely been applied to non-small-cell lung cancer (NSCLC) diagnosis. We developed...
Humans Multiomics Carcinoma, Non-Small-Cell Lung Deep Learning Algorithms Lung Neoplasms Early Detection of Cancer Biomarkers, Tumor
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Feasibility of a lung airway navigation system using fiber-Bragg shape sensing and artificial intelligence for early diagnosis of lung cancer.

PloS one Dec 7, 2022
Currently early diagnosis of malignant lesions at the periphery of lung parenchyma requires guidance of the biopsy needle catheter from the bronchoscope into the smaller peripheral airways via harmful X-ray radiation. Previously, we developed an imag...
Early Diagnosis Lung Lung Neoplasms Humans Artificial Intelligence
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