AIMC Topic: Lung Neoplasms

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GWO+RuleFit: rule-based explainable machine-learning combined with heuristics to predict mid-treatment FDG PET response to chemoradiation for locally advanced non-small cell lung cancer.

Physics in medicine and biology Jul 23, 2024
Vital rules learned from fluorodeoxyglucose positron emission tomography (FDG-PET) radiomics of tumor subregional response can provide clinical decision support for precise treatment adaptation. We combined a rule-based machine learning (ML) model (R...
Female Aged Male Middle Aged Humans Machine Learning Heuristics Positron-Emission Tomography Fluorodeoxyglucose F18 Chemoradiotherapy Image Processing, Computer-Assisted Lung Neoplasms Treatment Outcome Carcinoma, Non-Small-Cell Lung
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Machine learning and bioinformatics analysis of diagnostic biomarkers associated with the occurrence and development of lung adenocarcinoma.

PeerJ Jul 23, 2024
OBJECTIVE: Lung adenocarcinoma poses a major global health challenge and is a leading cause of cancer-related deaths worldwide. This study is a review of three molecular biomarkers screened by machine learning that are not only important in the occur...
Computational Biology Gene Expression Regulation, Neoplastic Databases, Genetic MicroRNAs Gene Expression Profiling Humans Adenocarcinoma of Lung Protein Interaction Maps Machine Learning Gene Regulatory Networks Biomarkers, Tumor Lung Neoplasms
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Differentiation of granulomatous nodules with lobulation and spiculation signs from solid lung adenocarcinomas using a CT deep learning model.

BMC cancer Jul 22, 2024
BACKGROUND: The diagnosis of solitary pulmonary nodules has always been a difficult and important point in clinical research, especially granulomatous nodules (GNs) with lobulation and spiculation signs, which are easily misdiagnosed as malignant tum...
Diagnosis, Differential Granuloma Adenocarcinoma of Lung Middle Aged Deep Learning Lung Neoplasms Solitary Pulmonary Nodule Humans Retrospective Studies Tomography, X-Ray Computed Female Aged Adult Male
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Endobronchial Ultrasound-Based Support Vector Machine Model for Differentiating between Benign and Malignant Mediastinal and Hilar Lymph Nodes.

Respiration; international review of thoracic diseases Jul 22, 2024
INTRODUCTION: The aim of the study was to establish an ultrasonographic radiomics machine learning model based on endobronchial ultrasound (EBUS) to assist in diagnosing benign and malignant mediastinal and hilar lymph nodes (LNs).
ROC Curve Aged Mediastinum Humans Lymphatic Metastasis Retrospective Studies Lung Neoplasms Bronchoscopy Female Lymph Nodes Diagnosis, Differential Adult Support Vector Machine Endosonography Male Middle Aged
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Plasma-based near-infrared spectroscopy for early diagnosis of lung cancer.

Journal of pharmaceutical and biomedical analysis Jul 21, 2024
Lung cancer (LC) continues to be a leading death cause in China, primarily due to late diagnosis. This study aimed to evaluate the effectiveness of using plasma-based near-infrared spectroscopy (NIRS) for LC early diagnosis. A total of 171 plasma sam...
Humans Machine Learning Algorithms Female Early Detection of Cancer Aged Case-Control Studies Least-Squares Analysis Adult Spectroscopy, Near-Infrared Male Lung Neoplasms Middle Aged Support Vector Machine
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Explainable lung cancer classification with ensemble transfer learning of VGG16, Resnet50 and InceptionV3 using grad-cam.

BMC medical imaging Jul 19, 2024
Medical imaging stands as a critical component in diagnosing various diseases, where traditional methods often rely on manual interpretation and conventional machine learning techniques. These approaches, while effective, come with inherent limitatio...
Humans Neural Networks, Computer Tomography, X-Ray Computed Deep Learning Lung Neoplasms
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Prediction of prognosis in lung cancer using machine learning with inter-institutional generalizability: A multicenter cohort study (WJOG15121L: REAL-WIND).

Lung cancer (Amsterdam, Netherlands) Jul 18, 2024
OBJECTIVES: Predicting the prognosis of lung cancer is crucial for providing optimal medical care. However, a method to accurately predict the overall prognosis in patients with stage IV lung cancer, even with the use of machine learning, has not bee...
Neoplasm Staging Middle Aged Cohort Studies ROC Curve Lung Neoplasms Humans Aged Machine Learning Aged, 80 and over Algorithms Male Prognosis Retrospective Studies Female
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Deep learning reconstruction for zero echo time lung magnetic resonance imaging: impact on image quality and lesion detection.

Clinical radiology Jul 17, 2024
AIMS: This study aimed to examine the impact of deep-learning reconstruction (DLR) on zero echo time (ZTE) lung MRI.
Lung Neoplasms Humans Magnetic Resonance Imaging Retrospective Studies Image Interpretation, Computer-Assisted Female Male Tomography, X-Ray Computed Phantoms, Imaging Aged Middle Aged Adult Lung Deep Learning
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Artificial intelligence-based plasma exosome label-free SERS profiling strategy for early lung cancer detection.

Analytical and bioanalytical chemistry Jul 17, 2024
As a lung cancer biomarker, exosomes were utilized for in vitro diagnosis to overcome the lack of sensitivity of conventional imaging and the potential harm caused by tissue biopsy. However, given the inherent heterogeneity of exosomes, the challenge...
Early Detection of Cancer Exosomes Humans Neural Networks, Computer Artificial Intelligence Biomarkers, Tumor Cell Line, Tumor Lung Neoplasms Spectrum Analysis, Raman Support Vector Machine
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Metaheuristic integrated machine learning classification of colon cancer using STFT LASSO and EHO feature extraction from microarray gene expressions.

Scientific reports Jul 17, 2024
The microarray gene expression data poses a tremendous challenge due to their curse of dimensionality problem. The sheer volume of features far surpasses available samples, leading to overfitting and reduced classification accuracy. Thus the dimensio...
Humans Machine Learning Algorithms Gene Expression Profiling Bayes Theorem Colonic Neoplasms Oligonucleotide Array Sequence Analysis Lung Neoplasms Fourier Analysis Gene Expression Regulation, Neoplastic Support Vector Machine
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