AIMC Topic: Lung Neoplasms
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Prognostic value of combining clinical factors, F-FDG PET-based intensity, volumetric features, and deep learning predictor in patients with EGFR-mutated lung adenocarcinoma undergoing targeted therapies: a cross-scanner and temporal validation study.
Annals of nuclear medicine
May 5, 2024
OBJECTIVE: To investigate the prognostic value of F-FDG PET-based intensity, volumetric features, and deep learning (DL) across different generations of PET scanners in patients with epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma...
ML3CNet: Non-local means-assisted automatic framework for lung cancer subtypes classification using histopathological images.
Computer methods and programs in biomedicine
May 4, 2024
BACKGROUND AND OBJECTIVE: Lung cancer (LC) has a high fatality rate that continuously affects human lives all over the world. Early detection of LC prolongs human life and helps to prevent the disease. Histopathological inspection is a common method ...
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...
The Classification of VOCs Based on Sensor Images Using a Lightweight Neural Network for Lung Cancer Diagnosis.
Sensors (Basel, Switzerland)
Apr 28, 2024
The application of artificial intelligence to point-of-care testing (POCT) disease detection has become a hot research field, in which breath detection, which detects the patient's exhaled VOCs, combined with sensor arrays of convolutional neural net...
AI-driven Characterization of Solid Pulmonary Nodules on CT Imaging for Enhanced Malignancy Prediction in Small-sized Lung Adenocarcinoma.
Clinical lung cancer
Apr 27, 2024
OBJECTIVES: Distinguishing solid nodules from nodules with ground-glass lesions in lung cancer is a critical diagnostic challenge, especially for tumors ≤2 cm. Human assessment of these nodules is associated with high inter-observer variability, whic...
Machine learning for predicting liver and/or lung metastasis in colorectal cancer: A retrospective study based on the SEER database.
European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Apr 27, 2024
OBJECTIVE: This study aims to establish a machine learning (ML) model for predicting the risk of liver and/or lung metastasis in colorectal cancer (CRC).
Ultrasound-based radiomics machine learning models for diagnosing cervical lymph node metastasis in patients with non-small cell lung cancer: a multicentre study.
BMC cancer
Apr 27, 2024
BACKGROUND: Cervical lymph node metastasis (LNM) is an important prognostic factor for patients with non-small cell lung cancer (NSCLC). We aimed to develop and validate machine learning models that use ultrasound radiomic and descriptive semantic fe...
A Pipeline for Evaluation of Machine Learning/Artificial Intelligence Models to Quantify Programmed Death Ligand 1 Immunohistochemistry.
Laboratory investigation; a journal of technical methods and pathology
Apr 26, 2024
Immunohistochemistry (IHC) is used to guide treatment decisions in multiple cancer types. For treatment with checkpoint inhibitors, programmed death ligand 1 (PD-L1) IHC is used as a companion diagnostic. However, the scoring of PD-L1 is complicated ...
A dual data stream hybrid neural network for classifying pathological images of lung adenocarcinoma.
Computers in biology and medicine
Apr 24, 2024
Lung cancer has seriously threatened human health due to its high lethality and morbidity. Lung adenocarcinoma, in particular, is one of the most common subtypes of lung cancer. Pathological diagnosis is regarded as the gold standard for cancer diagn...
Integrated Bioinformatics and Machine Learning Analysis Identify ACADL as a Potent Biomarker of Reactive Mesothelial Cells.
The American journal of pathology
Apr 22, 2024
Mesothelial cells with reactive hyperplasia are difficult to distinguish from malignant mesothelioma cells based on cell morphology. This study aimed to identify and validate potential biomarkers that distinguish mesothelial cells from mesothelioma c...
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