AIMC Topic: Lung Neoplasms
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KAMLN: A Knowledge-aware Multi-label Network for Lung Cancer Complication Prediction.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Surgical resection is now the only curative approach for early stage lung cancer patients. However, postoperative complications pose a significant threat to the health and life of patients. The current complication prediction methods usually ignore t...
Hard example mining in Multi-Instance Learning for Whole-Slide Image Classification.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Multiple instance learning(MIL) has shown superior performance in the classification of whole-slide images(WSIs). The implementation of multiple instance learning for WSI classification typically involves two components, i.e., a feature extractor, wh...
Unsupervised 3D Lung Segmentation by Leveraging 2D Segment Anything Model.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Lung segmentation is the first important step for lung nodule detection and lung cancer analysis. Deep neural networks have achieved state-of-the-art for most tasks in medical image analysis, including lung segmentation. However, training a deep lear...
Deciphering lung adenocarcinoma prognosis and immunotherapy response through an AI-driven stemness-related gene signature.
Journal of cellular and molecular medicine
Jul 1, 2024
Lung adenocarcinoma (LUAD) is a leading cause of cancer-related deaths, and improving prognostic accuracy is vital for personalised treatment approaches, especially in the context of immunotherapy. In this study, we constructed an artificial intellig...
Integrating machine learning and single-cell analysis to uncover lung adenocarcinoma progression and prognostic biomarkers.
Journal of cellular and molecular medicine
Jul 1, 2024
The progression of lung adenocarcinoma (LUAD) from atypical adenomatous hyperplasia (AAH) to invasive adenocarcinoma (IAC) involves a complex evolution of tumour cell clusters, the mechanisms of which remain largely unknown. By integrating single-cel...
Advancing lung adenocarcinoma prognosis and immunotherapy prediction with a multi-omics consensus machine learning approach.
Journal of cellular and molecular medicine
Jul 1, 2024
Lung adenocarcinoma (LUAD) is a tumour characterized by high tumour heterogeneity. Although there are numerous prognostic and immunotherapeutic options available for LUAD, there is a dearth of precise, individualized treatment plans. We integrated mR...
[Artificial intelligence research advances in discrimination and diagnosis of pulmonary ground-glass nodules].
Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases
Jun 12, 2024
Lung cancer, which accounts for about 18% of all cancer-related deaths worldwide, has a dismal 5-year survival rate of less than 20%. Survival rates for early-stage lung cancers (stages IA1, IA2, IA3, and IB, according to the TNM staging system) are ...
Improving Prediction of Survival and Progression in Metastatic Non-Small Cell Lung Cancer After Immunotherapy Through Machine Learning of Circulating Tumor DNA.
JCO precision oncology
Jun 1, 2024
PURPOSE: To use modern machine learning approaches to enhance and automate the feature extraction from the longitudinal circulating tumor DNA (ctDNA) data and to improve the prediction of survival and disease progression, risk stratification, and tre...
Machine learning and radiomics for predicting efficacy of programmed cell death protein 1 inhibitor for small cell lung cancer: A multicenter cohort study.
Clinical and translational medicine
Jun 1, 2024
Exploring Negated Entites for Named Entity Recognition in Italian Lung Cancer Clinical Reports.
Studies in health technology and informatics
May 23, 2024
This paper explores the potential of leveraging electronic health records (EHRs) for personalized health research through the application of artificial intelligence (AI) techniques, specifically Named Entity Recognition (NER). By extracting crucial p...
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