AIMC Topic: Lung Neoplasms
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Prognostication of lung adenocarcinomas using CT-based deep learning of morphological and histopathological features: a retrospective dual-institutional study.
European radiology
Oct 20, 2023
OBJECTIVES: To develop and validate CT-based deep learning (DL) models that learn morphological and histopathological features for lung adenocarcinoma prognostication, and to compare them with a previously developed DL discrete-time survival model.
Enlightening the path to NSCLC biomarkers: Utilizing the power of XAI-guided deep learning.
Computer methods and programs in biomedicine
Oct 20, 2023
BACKGROUND AND OBJECTIVE: The early diagnosis of Non-small cell lung cancer (NSCLC) is of prime importance to improve the patient's survivability and quality of life. Being a heterogeneous disease at the molecular and cellular level, the biomarkers r...
Comparison of clinical efficacy of da Vinci robot-assisted lung cancer surgery with two-, three- and four-hole approaches.
Updates in surgery
Oct 14, 2023
Orifice reduction strategies for da Vinci robotic surgery have been a hot topic of research in recent years. We retrospectively analyzed the perioperative outcomes of robotic-assisted thoracoscopic surgery (RATS) with two, three, and four-hole approa...
Development and Validation of a Deep Learning Radiomics Model to Predict High-Risk Pathologic Pulmonary Nodules Using Preoperative Computed Tomography.
Academic radiology
Oct 5, 2023
RATIONALE AND OBJECTIVES: To accurately identify the high-risk pathological factors of pulmonary nodules, our study constructed a model combined with clinical features, radiomics features, and deep transfer learning features to predict high-risk path...
Deep learning-based solid component measuring enabled interpretable prediction of tumor invasiveness for lung adenocarcinoma.
Lung cancer (Amsterdam, Netherlands)
Oct 5, 2023
BACKGROUND: The nature of the solid component of subsolid nodules (SSNs) can indicate tumor pathological invasiveness. However, preoperative solid component assessment still lacks a reference standard.
Beam mask and sliding window-facilitated deep learning-based accurate and efficient dose prediction for pencil beam scanning proton therapy.
Medical physics
Sep 25, 2023
BACKGROUND: Accurate and efficient dose calculation is essential for on-line adaptive planning in proton therapy. Deep learning (DL) has shown promising dose prediction results in photon therapy. However, there is a scarcity of DL-based dose predicti...
Extracting lung contour deformation features with deep learning for internal target motion tracking: a preliminary study.
Physics in medicine and biology
Sep 22, 2023
. To propose lung contour deformation features (LCDFs) as a surrogate to estimate the thoracic internal target motion, and to report their performance by correlating with the changing body using a cascade ensemble model (CEM). LCDFs, correlated to th...
A comparison of 18 F-FDG PET-based radiomics and deep learning in predicting regional lymph node metastasis in patients with resectable lung adenocarcinoma: a cross-scanner and temporal validation study.
Nuclear medicine communications
Sep 21, 2023
OBJECTIVE: The performance of 18 F-FDG PET-based radiomics and deep learning in detecting pathological regional nodal metastasis (pN+) in resectable lung adenocarcinoma varies, and their use across different generations of PET machines has not been t...
Imaging of Solid Pulmonary Nodules.
Clinics in chest medicine
Sep 19, 2023
Early detection with accurate classification of solid pulmonary nodules is critical in reducing lung cancer morbidity and mortality. Computed tomography (CT) remains the most widely used imaging examination for pulmonary nodule evaluation; however, o...
PET/CT-based deep learning grading signature to optimize surgical decisions for clinical stage I invasive lung adenocarcinoma and biologic basis under its prediction: a multicenter study.
European journal of nuclear medicine and molecular imaging
Sep 19, 2023
PURPOSE: No consensus on a grading system for invasive lung adenocarcinoma had been built over a long period of time. Until October 2020, a novel grading system was proposed to quantify the whole landscape of histologic subtypes and proportions of pu...
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