AIMC Topic: Lung Neoplasms
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Hessian Regularized -Nonnegative Matrix Factorization and Deep Learning for miRNA-Disease Associations Prediction.
Interdisciplinary sciences, computational life sciences
Dec 15, 2023
Since the identification of microRNAs (miRNAs), empirical research has demonstrated their crucial involvement in the functioning of organisms. Investigating miRNAs significantly bolsters efforts related to averting, diagnosing, and treating intricate...
Deep learning of cell spatial organizations identifies clinically relevant insights in tissue images.
Nature communications
Dec 11, 2023
Recent advancements in tissue imaging techniques have facilitated the visualization and identification of various cell types within physiological and pathological contexts. Despite the emergence of cell-cell interaction studies, there is a lack of me...
Robotic Versus Thoracoscopic Sub-lobar Resection for Octogenarians with Clinical Stage IA Non-small Cell Lung Cancer: A Propensity Score-Matched Real-World Study.
Annals of surgical oncology
Dec 10, 2023
BACKGROUND: Minimally invasive sub-lobectomy is sufficient in treating small early-stage non-small cell lung cancer (NSCLC). However, comparison of the feasibility and oncologic efficacy between robot-assisted thoracoscopic surgery (RATS) and video-a...
Fusion of laser-induced breakdown spectroscopy technology and deep learning: a new method to identify malignant and benign lung tumors with high accuracy.
Analytical and bioanalytical chemistry
Dec 8, 2023
Precisely distinguishing between malignant and benign lung tumors is pivotal for suggesting therapeutic strategies and enhancing prognosis, yet this differentiation remains a daunting task. The growth rates, metastatic potentials, and prognoses of be...
Secret learning for lung cancer diagnosis-a study with homomorphic encryption, texture analysis and deep learning.
Biomedical physics & engineering express
Dec 8, 2023
Advanced lung cancer diagnoses from radiographic images include automated detection of lung cancer from CT-Scan images of the lungs. Deep learning is a popular method for decision making which can be used to classify cancerous and non-cancerous lungs...
Artificial Intelligence-Powered Assessment of Pathologic Response to Neoadjuvant Atezolizumab in Patients With NSCLC: Results From the LCMC3 Study.
Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer
Dec 7, 2023
INTRODUCTION: Pathologic response (PathR) by histopathologic assessment of resected specimens may be an early clinical end point associated with long-term outcomes with neoadjuvant therapy. Digital pathology may improve the efficiency and precision o...
Deep learning-based conditional inpainting for restoration of artifact-affected 4D CT images.
Medical physics
Dec 6, 2023
BACKGROUND: 4D CT imaging is an essential component of radiotherapy of thoracic and abdominal tumors. 4D CT images are, however, often affected by artifacts that compromise treatment planning quality and image information reliability.
ASO Author Reflections: Should We Prefer Robotic over Thoracoscopic Surgery for Sublobar Resection in Octogenarians with Pulmonary Nodules ≤ 2 cm?
Annals of surgical oncology
Dec 6, 2023
Deep Learning-Guided Dosimetry for Mitigating Local Failure of Patients With Non-Small Cell Lung Cancer Receiving Stereotactic Body Radiation Therapy.
International journal of radiation oncology, biology, physics
Dec 5, 2023
PURPOSE: Non-small cell lung cancer (NSCLC) stereotactic body radiation therapy with 50 Gy/5 fractions is sometimes considered controversial, as the nominal biologically effective dose (BED) of 100 Gy is felt by some to be insufficient for long-term ...
Deep learning radiomics of multimodal ultrasound for classifying metastatic cervical lymphadenopathy into primary cancer sites: a feasibility study.
Ultraschall in der Medizin (Stuttgart, Germany : 1980)
Dec 5, 2023
PURPOSE: To investigate the feasibility of deep learning radiomics (DLR) based on multimodal ultrasound to differentiate the primary cancer sites of metastatic cervical lymphadenopathy (CLA).
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