AIMC Topic: Lung Neoplasms
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Omics-based deep learning approaches for lung cancer decision-making and therapeutics development.
Briefings in functional genomics
May 15, 2024
Lung cancer has been the most common and the leading cause of cancer deaths globally. Besides clinicopathological observations and traditional molecular tests, the advent of robust and scalable techniques for nucleic acid analysis has revolutionized ...
Establishment and validation of multiclassification prediction models for pulmonary nodules based on machine learning.
The clinical respiratory journal
May 1, 2024
BACKGROUND: Lung cancer is the leading cause of cancer-related death worldwide. This study aimed to establish novel multiclassification prediction models based on machine learning (ML) to predict the probability of malignancy in pulmonary nodules (PN...
Clinical Validation of Artificial Intelligence-Powered PD-L1 Tumor Proportion Score Interpretation for Immune Checkpoint Inhibitor Response Prediction in Non-Small Cell Lung Cancer.
JCO precision oncology
May 1, 2024
PURPOSE: Evaluation of PD-L1 tumor proportion score (TPS) by pathologists has been very impactful but is limited by factors such as intraobserver/interobserver bias and intratumor heterogeneity. We developed an artificial intelligence (AI)-powered an...
Artificial Intelligence Enhances NSCLC Care by Predicting Treatment Outcomes, Validating Neoadjuvant Therapies, and Improving Precision.
Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer
May 1, 2024
Assistive AI in Lung Cancer Screening: A Retrospective Multinational Study in the United States and Japan.
Radiology. Artificial intelligence
May 1, 2024
Purpose To evaluate the impact of an artificial intelligence (AI) assistant for lung cancer screening on multinational clinical workflows. Materials and Methods An AI assistant for lung cancer screening was evaluated on two retrospective randomized m...
[Prediction of recurrence-free survival in lung adenocarcinoma based on self-supervised pre-training and multi-task learning].
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Apr 25, 2024
Computed tomography (CT) imaging is a vital tool for the diagnosis and assessment of lung adenocarcinoma, and using CT images to predict the recurrence-free survival (RFS) of lung adenocarcinoma patients post-surgery is of paramount importance in tai...
Predicting Invasiveness of Lung Adenocarcinoma at Chest CT with Deep Learning Ternary Classification Models.
Radiology
Apr 1, 2024
Background Preoperative discrimination of preinvasive, minimally invasive, and invasive adenocarcinoma at CT informs clinical management decisions but may be challenging for classifying pure ground-glass nodules (pGGNs). Deep learning (DL) may improv...
Artificial intelligence in lung cancer screening: Detection, classification, prediction, and prognosis.
Cancer medicine
Apr 1, 2024
BACKGROUND: The exceptional capabilities of artificial intelligence (AI) in extracting image information and processing complex models have led to its recognition across various medical fields. With the continuous evolution of AI technologies based o...
D3EGFR: a webserver for deep learning-guided drug sensitivity prediction and drug response information retrieval for EGFR mutation-driven lung cancer.
Briefings in bioinformatics
Mar 27, 2024
As key oncogenic drivers in non-small-cell lung cancer (NSCLC), various mutations in the epidermal growth factor receptor (EGFR) with variable drug sensitivities have been a major obstacle for precision medicine. To achieve clinical-level drug recomm...
Minimally invasive surgery for clinical T4 non-small-cell lung cancer: national trends and outcomes.
European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery
Mar 1, 2024
OBJECTIVES: Recent randomized data support the perioperative benefits of minimally invasive surgery (MIS) for non-small-cell lung cancer (NSCLC). Its utility for cT4 tumours remains understudied. We, therefore, sought to analyse national trends and o...
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