AIMC Topic: Carcinoma, Non-Small-Cell Lung
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Prediction of Epidermal Growth Factor Receptor Mutation Subtypes in Non-Small Cell Lung Cancer From Hematoxylin and Eosin-Stained Slides Using Deep Learning.
Laboratory investigation; a journal of technical methods and pathology
Jun 11, 2024
Accurate assessment of epidermal growth factor receptor (EGFR) mutation status and subtype is critical for the treatment of non-small cell lung cancer patients. Conventional molecular testing methods for detecting EGFR mutations have limitations. In ...
Predicting Lymphovascular Invasion in Non-small Cell Lung Cancer Using Deep Convolutional Neural Networks on Preoperative Chest CT.
Academic radiology
Jun 6, 2024
RATIONALE AND OBJECTIVES: Lymphovascular invasion (LVI) plays a significant role in precise treatments of non-small cell lung cancer (NSCLC). This study aims to build a non-invasive LVI prediction diagnosis model by combining preoperative CT images w...
New vision of HookEfficientNet deep neural network: Intelligent histopathological recognition system of non-small cell lung cancer.
Computers in biology and medicine
Jun 4, 2024
BACKGROUND: Efficient and precise diagnosis of non-small cell lung cancer (NSCLC) is quite critical for subsequent targeted therapy and immunotherapy. Since the advent of whole slide images (WSIs), the transition from traditional histopathology to di...
Integration of deep learning and habitat radiomics for predicting the response to immunotherapy in NSCLC patients.
Cancer immunology, immunotherapy : CII
Jun 4, 2024
BACKGROUND: The non-invasive biomarkers for predicting immunotherapy response are urgently needed to prevent both premature cessation of treatment and ineffective extension. This study aimed to construct a non-invasive model for predicting immunother...
Preoperative evaluation of visceral pleural invasion in peripheral lung cancer utilizing deep learning technology.
Surgery today
May 23, 2024
PURPOSE: This study aimed to assess the efficiency of artificial intelligence (AI) in the detection of visceral pleural invasion (VPI) of lung cancer using high-resolution computed tomography (HRCT) images, which is challenging for experts because of...
Deep Learning
Lung Neoplasms
Carcinoma, Non-Small-Cell Lung
Neoplasm Invasiveness
Neoplasm Staging
Pleural Neoplasms
Preoperative Period
Pleura
Adult
Sensitivity and Specificity
Male
Middle Aged
Tomography, X-Ray Computed
Female
Aged
Aged, 80 and over
Humans
Artificial Intelligence
Retrospective Studies
Preoperatively predicting survival outcome for clinical stage IA pure-solid non-small cell lung cancer by radiomics-based machine learning.
The Journal of thoracic and cardiovascular surgery
May 22, 2024
OBJECTIVE: Clinical stage IA non-small cell lung cancer (NSCLC) showing a pure-solid appearance on computed tomography is associated with a worse prognosis. This study aimed to develop and validate machine-learning models using preoperative clinical ...
A novel machine learning model for efficacy prediction of immunotherapy-chemotherapy in NSCLC based on CT radiomics.
Computers in biology and medicine
May 21, 2024
Lung cancer is categorized into two main types: non-small cell lung cancer (NSCLC) and small cell lung cancer. Of these, NSCLC accounts for approximately 85% of all cases and encompasses varieties such as squamous cell carcinoma and adenocarcinoma. F...
Deep Learning Features and Metabolic Tumor Volume Based on PET/CT to Construct Risk Stratification in Non-small Cell Lung Cancer.
Academic radiology
May 12, 2024
RATIONALE AND OBJECTIVES: To build a risk stratification by incorporating PET/CT-based deep learning features and whole-body metabolic tumor volume (MTV), which was to make predictions about overall survival (OS) and progression-free survival (PFS) f...
Accuracy of machine learning in preoperative identification of genetic mutation status in lung cancer: A systematic review and meta-analysis.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
May 10, 2024
BACKGROUND AND PURPOSE: We performed this systematic review and meta-analysis to investigate the performance of ML in detecting genetic mutation status in NSCLC patients.
Identifying lncRNAs and mRNAs related to survival of NSCLC based on bioinformatic analysis and machine learning.
Aging
May 1, 2024
Non-small cell lung cancer (NSCLC) is the most common histopathological type, and it is purposeful for screening potential prognostic biomarkers for NSCLC. This study aims to identify the lncRNAs and mRNAs related to survival of non-small cell lung c...
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