AIMC Topic: Lung Neoplasms

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Real-World Outcomes of Patients with Advanced Epidermal Growth Factor Receptor-Mutated Non-Small Cell Lung Cancer in Canada Using Data Extracted by Large Language Model-Based Artificial Intelligence.

Current oncology (Toronto, Ont.) Apr 2, 2024
Real-world evidence for patients with advanced -mutated non-small cell lung cancer (NSCLC) in Canada is limited. This study's objective was to use previously validated DARWEN artificial intelligence (AI) to extract data from electronic heath records ...
Aged, 80 and over Adult Male Artificial Intelligence Female Aged Treatment Outcome Carcinoma, Non-Small-Cell Lung Mutation ErbB Receptors Middle Aged Lung Neoplasms Canada Humans
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Deceptive learning in histopathology.

Histopathology Mar 31, 2024
AIMS: Deep learning holds immense potential for histopathology, automating tasks that are simple for expert pathologists and revealing novel biology for tasks that were previously considered difficult or impossible to solve by eye alone. However, the...
Humans Neural Networks, Computer Adenocarcinoma of Lung Deep Learning Lung Neoplasms Mutation
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Enhancing a deep learning model for pulmonary nodule malignancy risk estimation in chest CT with uncertainty estimation.

European radiology Mar 27, 2024
OBJECTIVE: To investigate the effect of uncertainty estimation on the performance of a Deep Learning (DL) algorithm for estimating malignancy risk of pulmonary nodules.
Retrospective Studies Tomography, X-Ray Computed Humans Algorithms Lung Neoplasms Female Middle Aged Multiple Pulmonary Nodules Aged Risk Assessment Solitary Pulmonary Nodule Male Deep Learning Radiographic Image Interpretation, Computer-Assisted Uncertainty
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A deep learning model for translating CT to ventilation imaging: analysis of accuracy and impact on functional avoidance radiotherapy planning.

Japanese journal of radiology Mar 27, 2024
PURPOSE: Radiotherapy planning incorporating functional lung images has the potential to reduce pulmonary toxicity. Free-breathing 4DCT-derived ventilation image (CTVI) may help quantify lung function. This study introduces a novel deep-learning mode...
Carcinoma, Non-Small-Cell Lung Radiotherapy Planning, Computer-Assisted Four-Dimensional Computed Tomography Lung Deep Learning Lung Neoplasms Aged Humans Male Tomography, X-Ray Computed Middle Aged Female
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Lung CT harmonization of paired reconstruction kernel images using generative adversarial networks.

Medical physics Mar 26, 2024
BACKGROUND: The kernel used in CT image reconstruction is an important factor that determines the texture of the CT image. Consistency of reconstruction kernel choice is important for quantitative CT-based assessment as kernel differences can lead to...
Humans Tomography, X-Ray Computed Deep Learning Lung Neoplasms
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Robust deep learning from incomplete annotation for accurate lung nodule detection.

Computers in biology and medicine Mar 26, 2024
Deep learning plays a significant role in the detection of pulmonary nodules in low-dose computed tomography (LDCT) scans, contributing to the diagnosis and treatment of lung cancer. Nevertheless, its effectiveness often relies on the availability of...
Radiographic Image Interpretation, Computer-Assisted Deep Learning Lung Neoplasms Solitary Pulmonary Nodule Humans Lung
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Comparing deep learning and pathologist quantification of cell-level PD-L1 expression in non-small cell lung cancer whole-slide images.

Scientific reports Mar 26, 2024
Programmed death-ligand 1 (PD-L1) expression is currently used in the clinic to assess eligibility for immune-checkpoint inhibitors via the tumor proportion score (TPS), but its efficacy is limited by high interobserver variability. Multiple papers h...
Carcinoma, Non-Small-Cell Lung Pathologists Immunohistochemistry Deep Learning Humans Lung Neoplasms Biomarkers, Tumor B7-H1 Antigen
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Enhancing Lung Nodule Classification: A Novel CViEBi-CBGWO Approach with Integrated Image Preprocessing.

Journal of imaging informatics in medicine Mar 25, 2024
Cancer detection and accurate classification pose significant challenges for medical professionals, as it is described as a lethal illness. Diagnosing the malignant lung nodules in its initial stage significantly enhances the recovery and survival ra...
Lung Neoplasms Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Lung Image Processing, Computer-Assisted Neural Networks, Computer Algorithms Humans
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Non-invasive prediction for pathologic complete response to neoadjuvant chemoimmunotherapy in lung cancer using CT-based deep learning: a multicenter study.

Frontiers in immunology Mar 25, 2024
Neoadjuvant chemoimmunotherapy has revolutionized the therapeutic strategy for non-small cell lung cancer (NSCLC), and identifying candidates likely responding to this advanced treatment is of important clinical significance. The current multi-instit...
Immunotherapy Pathologic Complete Response Tumor Microenvironment Humans Neoadjuvant Therapy Retrospective Studies Deep Learning Carcinoma, Non-Small-Cell Lung Tomography, X-Ray Computed Lung Neoplasms
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Dual-Region Computed Tomography Radiomics-Based Machine Learning Predicts Subcarinal Lymph Node Metastasis in Patients with Non-small Cell Lung Cancer.

Annals of surgical oncology Mar 23, 2024
BACKGROUND: Noninvasively and accurately predicting subcarinal lymph node metastasis (SLNM) for patients with non-small cell lung cancer (NSCLC) remains challenging. This study was designed to develop and validate a tumor and subcarinal lymph nodes (...
Retrospective Studies Tomography, X-Ray Computed Female Aged Humans Machine Learning Prognosis Lymph Nodes Male Carcinoma, Non-Small-Cell Lung Pneumonectomy Middle Aged Aged, 80 and over Follow-Up Studies Lymphatic Metastasis Adult Lung Neoplasms Lymph Node Excision Radiomics
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