AIMC Topic: Lung Neoplasms

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Transformer-based deep learning model for the diagnosis of suspected lung cancer in primary care based on electronic health record data.

EBioMedicine Nov 13, 2024
BACKGROUND: Due to its late stage of diagnosis lung cancer is the commonest cause of death from cancer in the UK. Existing epidemiological risk models in clinical usage, which have Positive Predictive Values (PPV) of less than 10%, do not consider th...
Humans Aged Electronic Health Records Male Female Middle Aged Case-Control Studies Primary Health Care Deep Learning Lung Neoplasms ROC Curve Early Detection of Cancer
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A novel benign and malignant classification model for lung nodules based on multi-scale interleaved fusion integrated network.

Scientific reports Nov 11, 2024
One of the precursors of lung cancer is the presence of lung nodules, and accurate identification of their benign or malignant nature is important for the long-term survival of patients. With the development of artificial intelligence, deep learning ...
Algorithms Solitary Pulmonary Nodule Deep Learning Lung Neoplasms Humans Neural Networks, Computer
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Predictive analytics of complex healthcare systems using deep learning based disease diagnosis model.

Scientific reports Nov 11, 2024
Cancer is a life-threatening disease resulting from a genetic disorder and a range of metabolic anomalies. In particular, lung and colon cancer (LCC) are among the major causes of death and disease in humans. The histopathological diagnoses are criti...
Lung Neoplasms Colonic Neoplasms Diagnosis, Computer-Assisted Deep Learning Humans Neural Networks, Computer Algorithms Delivery of Health Care
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Imaging error reduction in radial cine-MRI with deep learning-based intra-frame motion compensation.

Physics in medicine and biology Nov 11, 2024
Radial cine-MRI allows for sliding window reconstruction at nearly arbitrary frame rate, promising high-speed imaging for intra-fractional motion monitoring in magnetic resonance guided radiotherapy. However, motion within the reconstruction window m...
Phantoms, Imaging Movement Magnetic Resonance Imaging, Cine Image Processing, Computer-Assisted Lung Neoplasms Humans Deep Learning
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Integrating radiomic and 3D autoencoder-based features for Non-Small Cell Lung Cancer survival analysis.

Computer methods and programs in biomedicine Nov 8, 2024
BACKGROUND AND OBJECTIVES: The aim of this study is to develop a radiomic and deep learning-based signature for survival analysis of patients with Non-Small Cell Lung Cancer.
Lung Neoplasms Carcinoma, Non-Small-Cell Lung Survival Analysis Proportional Hazards Models Middle Aged Deep Learning Imaging, Three-Dimensional Radiomics Humans Male Female Aged
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Mitigating Diagnostic Errors in Lung Cancer Classification: A Multi-Eyes Principle to Uncertainty Quantification.

IEEE journal of biomedical and health informatics Nov 6, 2024
In radiology, particularly in lung cancer diagnosis, diagnostic errors and cognitive biases pose substantial challenges. These issues, including perceptual errors, interpretive mistakes, and cognitive biases such as anchoring and premature closure, a...
Lung Neoplasms Monte Carlo Method Uncertainty Humans Diagnostic Errors Deep Learning
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Association of artificial intelligence-based immunoscore with the efficacy of chemoimmunotherapy in patients with advanced non-squamous non-small cell lung cancer: a multicentre retrospective study.

Frontiers in immunology Nov 6, 2024
PURPOSE: Currently, chemoimmunotherapy is effective only in a subset of patients with advanced non-squamous non-small cell lung cancer. Robust biomarkers for predicting the efficacy of chemoimmunotherapy would be useful to identify patients who would...
Carcinoma, Non-Small-Cell Lung Biomarkers, Tumor Male Middle Aged Antineoplastic Combined Chemotherapy Protocols Retrospective Studies Treatment Outcome Female Lung Neoplasms Humans Aged Immunotherapy Artificial Intelligence
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Non-small cell lung cancer detection through knowledge distillation approach with teaching assistant.

PloS one Nov 6, 2024
Non-small cell lung cancer (NSCLC) exhibits a comparatively slower rate of metastasis in contrast to small cell lung cancer, contributing to approximately 85% of the global patient population. In this work, leveraging CT scan images, we deploy a know...
Humans Tomography, X-Ray Computed Deep Learning Lung Neoplasms Carcinoma, Non-Small-Cell Lung
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Enhanced NSCLC subtyping and staging through attention-augmented multi-task deep learning: A novel diagnostic tool.

International journal of medical informatics Nov 5, 2024
OBJECTIVES: The objective of this study is to develop a novel multi-task learning approach with attention encoders for classifying histologic subtypes and clinical stages of non-small cell lung cancer (NSCLC), with superior performance compared to cu...
Humans Male Middle Aged Deep Learning Tomography, X-Ray Computed Female Aged Neoplasm Staging Lung Neoplasms Carcinoma, Non-Small-Cell Lung
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Predicting radiation pneumonitis in lung cancer using machine learning and multimodal features: a systematic review and meta-analysis of diagnostic accuracy.

BMC cancer Nov 5, 2024
OBJECTIVES: To evaluate the diagnostic accuracy of machine learning models incorporating multimodal features for predicting radiation pneumonitis in lung cancer through a systematic review and meta-analysis.
Sensitivity and Specificity Lung Neoplasms Radiation Pneumonitis Humans Machine Learning
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