Small Cell Lung Carcinoma

Novel radiomic features versus deep learning: differentiating brain metastases from pathological lung cancer types in small datasets.

The British journal of radiology 37129296

OBJECTIVE: Accurate diagnosis and early treatment are crucial for survival in patients with brain metastases. This study aims to expand the capability of radiomics-based classification algorithms with novel features and compare results with deep lear...

Adenocarcinoma Brain Neoplasms Deep Learning Humans Lung Neoplasms Small Cell Lung Carcinoma

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Comparison Results of Three-Port Robot-Assisted and Uniportal Video-Assisted Lobectomy for Functional Recovery Index in the Treatment of Early Stage Non-small Cell Lung Cancer: A Propensity Score-Matched Analysis.

Annals of surgical oncology 38105381

BACKGROUND: Minimally invasive lobectomy is the standard treatment for early stage non-small cell lung cancer (NSCLC). The aim of this study is to investigate postoperative recovery in a prospective trial of discharged patients with early stage non-s...

Carcinoma, Non-Small-Cell Lung Cough Humans Lung Neoplasms Pneumonectomy Propensity Score Prospective Studies Robotics Small Cell Lung Carcinoma Thoracic Surgery, Video-Assisted

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Identifying Pathological Subtypes of Brain Metastasis from Lung Cancer Using MRI-Based Deep Learning Approach: A Multicenter Study.

Journal of imaging informatics in medicine 38347392

The aim of this study was to investigate the feasibility of deep learning (DL) based on multiparametric MRI to differentiate the pathological subtypes of brain metastasis (BM) in lung cancer patients. This retrospective analysis collected 246 patient...

Adult Aged Brain Brain Neoplasms Carcinoma, Non-Small-Cell Lung Deep Learning Feasibility Studies Female Humans Image Interpretation, Computer-Assisted Lung Neoplasms Magnetic Resonance Imaging Male Middle Aged Retrospective Studies ROC Curve Small Cell Lung Carcinoma

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Predicting overall survival and prophylactic cranial irradiation benefit in small-cell lung cancer with CT-based deep learning: A retrospective multicenter study.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology 38479441

BACKGROUND AND PURPOSE: To develop a computed tomography (CT)-based deep learning model to predict overall survival (OS) among small-cell lung cancer (SCLC) patients and identify patients who could benefit from prophylactic cranial irradiation (PCI) ...

Aged Cranial Irradiation Deep Learning Female Humans Lung Neoplasms Male Middle Aged Retrospective Studies Small Cell Lung Carcinoma Survival Rate Tomography, X-Ray Computed

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Precise and automated lung cancer cell classification using deep neural network with multiscale features and model distillation.

Scientific reports 38714840

Lung diseases globally impose a significant pathological burden and mortality rate, particularly the differential diagnosis between adenocarcinoma, squamous cell carcinoma, and small cell lung carcinoma, which is paramount in determining optimal trea...

Adenocarcinoma Carcinoma, Squamous Cell Deep Learning Diagnosis, Differential Humans Image Processing, Computer-Assisted Lung Neoplasms Neural Networks, Computer Small Cell Lung Carcinoma

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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 38840331

Aged Cohort Studies Female Humans Immune Checkpoint Inhibitors Lung Neoplasms Machine Learning Male Middle Aged Programmed Cell Death 1 Receptor Radiomics Small Cell Lung Carcinoma Treatment Outcome

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Identification of effective diagnostic genes and immune cell infiltration characteristics in small cell lung cancer by integrating bioinformatics analysis and machine learning algorithms.

Saudi medical journal 39074893

OBJECTIVES: To identify potential diagnostic markers for small cell lung cancer (SCLC) and investigate the correlation with immune cell infiltration.

Algorithms Biomarkers, Tumor Computational Biology Gene Expression Profiling Gene Ontology Humans Lung Neoplasms Machine Learning Small Cell Lung Carcinoma

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Machine learning-based prediction model for brain metastasis in patients with extensive-stage small cell lung cancer.

Scientific reports 39567766

Brain metastases (BMs) in extensive-stage small cell lung cancer (ES-SCLC) are often associated with poor survival rates and quality of life, making the timely identification of high-risk patients for BMs in ES-SCLC crucial. Patients diagnosed with E...

Adult Aged Algorithms Brain Neoplasms Female Humans Lung Neoplasms Machine Learning Male Middle Aged Neoplasm Staging Prognosis Risk Factors ROC Curve SEER Program Small Cell Lung Carcinoma

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Identification of key gene signatures for predicting chemo-immunotherapy efficacy in extensive-stage small-cell lung cancer using machine learning.

Lung cancer (Amsterdam, Netherlands) 39787635

OBJECTIVES: The lack of definitive biomarkers presents a significant challenge for chemo-immunotherapy in extensive-stage small-cell lung cancer (ES-SCLC). We aimed to identify key genes associated with chemo-immunotherapy efficacy in ES-SCLC through...

Aged Antineoplastic Combined Chemotherapy Protocols Biomarkers, Tumor Female Gene Expression Profiling Gene Expression Regulation, Neoplastic Humans Immunotherapy Lung Neoplasms Machine Learning Male Middle Aged Neoplasm Staging Prognosis Prospective Studies Small Cell Lung Carcinoma Transcriptome Treatment Outcome

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Model development and validation for predicting small-cell lung cancer bone metastasis utilizing diverse machine learning algorithms based on the SEER database.

Medicine 40128015

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...

Adult Aged Algorithms Bone Neoplasms Female Humans Lung Neoplasms Machine Learning Male Middle Aged ROC Curve SEER Program Small Cell Lung Carcinoma

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Explore the latest research on artificial intelligence and machine learning in medicine.

Novel radiomic features versus deep learning: differentiating brain metastases from pathological lung cancer types in small datasets.

Comparison Results of Three-Port Robot-Assisted and Uniportal Video-Assisted Lobectomy for Functional Recovery Index in the Treatment of Early Stage Non-small Cell Lung Cancer: A Propensity Score-Matched Analysis.

Identifying Pathological Subtypes of Brain Metastasis from Lung Cancer Using MRI-Based Deep Learning Approach: A Multicenter Study.

Predicting overall survival and prophylactic cranial irradiation benefit in small-cell lung cancer with CT-based deep learning: A retrospective multicenter study.

Precise and automated lung cancer cell classification using deep neural network with multiscale features and model distillation.

Machine learning and radiomics for predicting efficacy of programmed cell death protein 1 inhibitor for small cell lung cancer: A multicenter cohort study.

Identification of effective diagnostic genes and immune cell infiltration characteristics in small cell lung cancer by integrating bioinformatics analysis and machine learning algorithms.

Machine learning-based prediction model for brain metastasis in patients with extensive-stage small cell lung cancer.

Identification of key gene signatures for predicting chemo-immunotherapy efficacy in extensive-stage small-cell lung cancer using machine learning.

Model development and validation for predicting small-cell lung cancer bone metastasis utilizing diverse machine learning algorithms based on the SEER database.

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