AIMC Topic: Lung Neoplasms
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Systematic review and meta-analysis of deep learning applications in computed tomography lung cancer segmentation.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
May 26, 2024
BACKGROUND: Accurate segmentation of lung tumors on chest computed tomography (CT) scans is crucial for effective diagnosis and treatment planning. Deep Learning (DL) has emerged as a promising tool in medical imaging, particularly for lung cancer se...
A deep learning-based radiomics model for predicting lymph node status from lung adenocarcinoma.
BMC medical imaging
May 24, 2024
OBJECTIVES: At present, there are many limitations in the evaluation of lymph node metastasis of lung adenocarcinoma. Currently, there is a demand for a safe and accurate method to predict lymph node metastasis of lung cancer. In this study, radiomic...
Preoperative evaluation of visceral pleural invasion in peripheral lung cancer utilizing deep learning technology.
Surgery today
May 23, 2024
PURPOSE: This study aimed to assess the efficiency of artificial intelligence (AI) in the detection of visceral pleural invasion (VPI) of lung cancer using high-resolution computed tomography (HRCT) images, which is challenging for experts because of...
Pleura
Neoplasm Staging
Pleural Neoplasms
Preoperative Period
Sensitivity and Specificity
Male
Middle Aged
Carcinoma, Non-Small-Cell Lung
Neoplasm Invasiveness
Deep Learning
Lung Neoplasms
Aged
Aged, 80 and over
Adult
Retrospective Studies
Tomography, X-Ray Computed
Female
Humans
Artificial Intelligence
Deep Learning Models for Predicting Malignancy Risk in CT-Detected Pulmonary Nodules: A Systematic Review and Meta-analysis.
Lung
May 23, 2024
BACKGROUND: There has been growing interest in using artificial intelligence/deep learning (DL) to help diagnose prevalent diseases earlier. In this study we sought to survey the landscape of externally validated DL-based computer-aided diagnostic (C...
Artificial Intelligence and Lung Pathology.
Advances in anatomic pathology
May 23, 2024
This manuscript provides a comprehensive overview of the application of artificial intelligence (AI) in lung pathology, particularly in the diagnosis of lung cancer. It discusses various AI models designed to support pathologists and clinicians. AI m...
Masked hypergraph learning for weakly supervised histopathology whole slide image classification.
Computer methods and programs in biomedicine
May 23, 2024
BACKGROUND AND OBJECTIVES: Graph neural network (GNN) has been extensively used in histopathology whole slide image (WSI) analysis due to the efficiency and flexibility in modelling relationships among entities. However, most existing GNN-based WSI a...
Preoperatively predicting survival outcome for clinical stage IA pure-solid non-small cell lung cancer by radiomics-based machine learning.
The Journal of thoracic and cardiovascular surgery
May 22, 2024
OBJECTIVE: Clinical stage IA non-small cell lung cancer (NSCLC) showing a pure-solid appearance on computed tomography is associated with a worse prognosis. This study aimed to develop and validate machine-learning models using preoperative clinical ...
Standalone deep learning versus experts for diagnosis lung cancer on chest computed tomography: a systematic review.
European radiology
May 22, 2024
PURPOSE: To compare the diagnostic performance of standalone deep learning (DL) algorithms and human experts in lung cancer detection on chest computed tomography (CT) scans.
Pre-operative lung ablation prediction using deep learning.
European radiology
May 22, 2024
OBJECTIVE: Microwave lung ablation (MWA) is a minimally invasive and inexpensive alternative cancer treatment for patients who are not candidates for surgery/radiotherapy. However, a major challenge for MWA is its relatively high tumor recurrence rat...
Machine learning-based integration develops an immunogenic cell death-derived lncRNA signature for predicting prognosis and immunotherapy response in lung adenocarcinoma.
Scientific reports
May 22, 2024
Accumulating evidence demonstrates that lncRNAs are involved in the regulation of the immune microenvironment and early tumor development. Immunogenic cell death occurs mainly through the release or increase of tumor-associated antigen and tumor-spec...
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