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Small Cell Lung Carcinoma

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Use of an Artificial Neural Network to Construct a Model of Predicting Deep Fungal Infection in Lung Cancer Patients.

Asian Pacific journal of cancer prevention : APJCP 26163648
BACKGROUND: The statistical methods to analyze and predict the related dangerous factors of deep fungal infection in lung cancer patients were several, such as logic regression analysis, meta-analysis, multivariate Cox proportional hazards model anal...
Adenocarcinoma Adult Aged Aged, 80 and over Carcinoma, Large Cell Carcinoma, Non-Small-Cell Lung Carcinoma, Squamous Cell Cross Infection Female Follow-Up Studies Fungi Humans Incidence Logistic Models Lung Neoplasms Male Middle Aged Mycoses Neoplasm Staging Neural Networks, Computer Prognosis Retrospective Studies Risk Factors ROC Curve Small Cell Lung Carcinoma
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Application of an artificial neural network model for selection of potential lung cancer biomarkers.

Journal of breath research 25944812
Determination of volatile organic compounds (VOCs) in the exhaled breath samples of lung cancer patients and healthy controls was carried out by SPME-GC/MS (solid phase microextraction- gas chromatography combined with mass spectrometry) analyses. In...
Adenocarcinoma Adult Aged Aged, 80 and over Biomarkers, Tumor Breath Tests Carcinoma, Non-Small-Cell Lung Case-Control Studies Exhalation Female Gas Chromatography-Mass Spectrometry Humans Lung Neoplasms Male Mass Spectrometry Middle Aged Neural Networks, Computer Sensitivity and Specificity Small Cell Lung Carcinoma Smoking Solid Phase Microextraction Volatile Organic Compounds Young Adult
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Evaluation of Machine Learning Algorithm Utilization for Lung Cancer Classification Based on Gene Expression Levels.

Asian Pacific journal of cancer prevention : APJCP 26925688
BACKGROUND: Lung cancer remains one of the most common cancers in the world, both in terms of new cases (about 13% of total per year) and deaths (nearly one cancer death in five), because of the high case fatality. Errors in lung cancer type or malig...
Adenocarcinoma Algorithms Biomarkers, Tumor Carcinoma, Squamous Cell Case-Control Studies Databases, Factual Decision Trees Gene Expression Profiling Humans Lung Neoplasms Machine Learning Small Cell Lung Carcinoma Support Vector Machine
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Differentiating Small-Cell Lung Cancer From Non-Small-Cell Lung Cancer Brain Metastases Based on MRI Using Efficientnet and Transfer Learning Approach.

Technology in cancer research & treatment 34030542
Differentiation between small-cell lung cancer (SCLC) from non-small-cell lung cancer (NSCLC) brain metastases is crucial due to the different clinical behaviors of the two tumor types. We propose the use of a deep learning and transfer learning appr...
Brain Neoplasms Carcinoma, Non-Small-Cell Lung Diagnosis, Differential Female Follow-Up Studies Humans Image Interpretation, Computer-Assisted Lung Neoplasms Machine Learning Magnetic Resonance Imaging Male Middle Aged Prognosis Retrospective Studies ROC Curve Small Cell Lung Carcinoma
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A Novel Graph Neural Network Methodology to Investigate Dihydroorotate Dehydrogenase Inhibitors in Small Cell Lung Cancer.

Biomolecules 33806898
Small cell lung cancer (SCLC) is a particularly aggressive tumor subtype, and dihydroorotate dehydrogenase (DHODH) has been demonstrated to be a therapeutic target for SCLC. Network pharmacology analysis and virtual screening were utilized to find ou...
Algorithms Dihydroorotate Dehydrogenase Humans Machine Learning Molecular Docking Simulation Neural Networks, Computer Oxidoreductases Acting on CH-CH Group Donors Small Cell Lung Carcinoma
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A deep learning model for the classification of indeterminate lung carcinoma in biopsy whole slide images.

Scientific reports 33854137
The differentiation between major histological types of lung cancer, such as adenocarcinoma (ADC), squamous cell carcinoma (SCC), and small-cell lung cancer (SCLC) is of crucial importance for determining optimum cancer treatment. Hematoxylin and Eos...
Adenocarcinoma Area Under Curve Carcinoma, Squamous Cell Databases, Factual Deep Learning Humans Lung Lung Neoplasms ROC Curve Small Cell Lung Carcinoma
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Weakly supervised learning for classification of lung cytological images using attention-based multiple instance learning.

Scientific reports 34645863
In cytological examination, suspicious cells are evaluated regarding malignancy and cancer type. To assist this, we previously proposed an automated method based on supervised learning that classifies cells in lung cytological images as benign or mal...
Adenocarcinoma Carcinoma, Squamous Cell Chromatin Deep Learning Humans Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Lung Lung Neoplasms Medical Informatics Neural Networks, Computer Pattern Recognition, Automated Reproducibility of Results Retrospective Studies Small Cell Lung Carcinoma Supervised Machine Learning Thorax
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Classification of subtypes including LCNEC in lung cancer biopsy slides using convolutional neural network from scratch.

Scientific reports 35115593
Identifying the lung carcinoma subtype in small biopsy specimens is an important part of determining a suitable treatment plan but is often challenging without the help of special and/or immunohistochemical stains. Pathology image analysis that tackl...
Adenocarcinoma of Lung Area Under Curve Biopsy Carcinoma, Non-Small-Cell Lung Carcinoma, Squamous Cell Datasets as Topic Eosine Yellowish-(YS) Hematoxylin Histocytochemistry Humans Image Interpretation, Computer-Assisted Lung Lung Neoplasms Neural Networks, Computer Small Cell Lung Carcinoma
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