AIMC Topic: Lung Neoplasms
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Identification of a Biomarker Panel in Extracellular Vesicles Derived From Non-Small Cell Lung Cancer (NSCLC) Through Proteomic Analysis and Machine Learning.
Journal of extracellular vesicles
May 1, 2025
Antigen fingerprint profiling of tumour-derived extracellular vesicles (TDEVs) in the body fluids is a promising strategy for identifying tumour biomarkers. In this study, proteomic and immunological assays reveal significantly higher CD155 levels in...
Artificial intelligence-driven microsatellite instability profiling reveals distinctive genetic features in patients with lung cancer.
Cancer
May 1, 2025
BACKGROUND: Microsatellite instability (MSI) has emerged as a predictive biomarker for immunotherapy response in various cancers, but its role in non-small cell lung cancer (NSCLC) is not fully understood.
Predicting Respiratory Disease Mortality Risk Using Open-Source AI on Chest Radiographs in an Asian Health Screening Population.
Radiology. Artificial intelligence
May 1, 2025
Purpose To assess the prognostic value of an open-source deep learning-based chest radiographs algorithm, CXR-Lung-Risk, for stratifying respiratory disease mortality risk among an Asian health screening population using baseline and follow-up chest ...
PD-L1 Scoring Models for Non-Small Cell Lung Cancer in China: Current Status, AI-Assisted Solutions and Future Perspectives.
Thoracic cancer
Apr 1, 2025
Immunotherapy has revolutionized the diagnosis and treatment model for patients with advanced non-small cell lung cancer (NSCLC). Numerous clinical trials and real-world reports have confirmed that PD-L1 status is a key factor for the successful use ...
Machine Learning Unveils Sphingolipid Metabolism's Role in Tumour Microenvironment and Immunotherapy in Lung Cancer.
Journal of cellular and molecular medicine
Apr 1, 2025
TME is a core player in the development of a cancerous lesion, the immune evasive potential of the lesion, and its response to therapy. Sphingolipid metabolism, which governs a number of cellular processes, has been recognised as a player involved in...
MoLPre: A Machine Learning Model to Predict Metastasis of cT1 Solid Lung Cancer.
Clinical and translational science
Apr 1, 2025
Given that more than 20% of patients with cT1 solid NSCLC showed nodal or extrathoracic metastasis, early detection of metastasis is crucial and urgent for improving therapeutic planning and patients' risk stratification in clinical practice. This st...
Deep Learning-Based Computer-Aided Diagnosis in Coronary Artery Calcium-Scoring CT for Pulmonary Nodule Detection: A Preliminary Study.
Yonsei medical journal
Apr 1, 2025
PURPOSE: To evaluate the feasibility and utility of deep learning-based computer-aided diagnosis (DL-CAD) for the detection of pulmonary nodules on coronary artery calcium (CAC)-scoring computed tomography (CT).
Evaluating robustly standardized explainable anomaly detection of implausible variables in cancer data.
Journal of the American Medical Informatics Association : JAMIA
Apr 1, 2025
OBJECTIVES: Explanations help to understand why anomaly detection algorithms identify data as anomalous. This study evaluates whether robustly standardized explanation scores correctly identify the implausible variables that make cancer data anomalou...
Model development and validation for predicting small-cell lung cancer bone metastasis utilizing diverse machine learning algorithms based on the SEER database.
Medicine
Mar 21, 2025
The aim of this study was to devise a machine learning algorithm with superior performance in predicting bone metastasis (BM) in small cell lung cancer (SCLC) and create a straightforward web-based predictor based on the developed algorithm. Data com...
[Application Practice of AI Empowering Post-discharge Specialized Disease Management in Postoperative Rehabilitation of the Lung Cancer Patients Undergoing Surgery].
Zhongguo fei ai za zhi = Chinese journal of lung cancer
Mar 20, 2025
BACKGROUND: Lung cancer is the leading malignancy in China in terms of both incidence and mortality. With increased health awareness and the widespread use of low-dose computed tomography (CT), early diagnosis rates have been steadily improving. Surg...
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