AIMC Topic: Lung Neoplasms

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PET radiomics-based lymphovascular invasion prediction in lung cancer using multiple segmentation and multi-machine learning algorithms.

Physical and engineering sciences in medicine Sep 3, 2024
The current study aimed to predict lymphovascular invasion (LVI) using multiple machine learning algorithms and multi-segmentation positron emission tomography (PET) radiomics in non-small cell lung cancer (NSCLC) patients, offering new avenues for p...
Female Aged Adult Radiomics Humans Machine Learning Algorithms Male Middle Aged ROC Curve Image Processing, Computer-Assisted Lung Neoplasms Carcinoma, Non-Small-Cell Lung Neoplasm Invasiveness Positron-Emission Tomography
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Deep learning-assisted interactive contouring of lung cancer: Impact on contouring time and consistency.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Sep 3, 2024
BACKGROUND AND PURPOSE: To evaluate the impact of a deep learning (DL)-assisted interactive contouring tool on inter-observer variability and the time taken to complete tumour contouring.
Radiotherapy Planning, Computer-Assisted Tumor Burden Observer Variation Humans Deep Learning Time Factors Lung Neoplasms Carcinoma, Non-Small-Cell Lung Positron Emission Tomography Computed Tomography
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Non-invasive multimodal CT deep learning biomarker to predict pathological complete response of non-small cell lung cancer following neoadjuvant immunochemotherapy: a multicenter study.

Journal for immunotherapy of cancer Sep 3, 2024
OBJECTIVES: Although neoadjuvant immunochemotherapy has been widely applied in non-small cell lung cancer (NSCLC), predicting treatment response remains a challenge. We used pretreatment multimodal CT to explore deep learning-based immunochemotherapy...
Tomography, X-Ray Computed Female Aged Male Humans Retrospective Studies Immunotherapy Neoadjuvant Therapy Carcinoma, Non-Small-Cell Lung Multimodal Imaging Middle Aged Deep Learning Lung Neoplasms
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Exploiting histopathological imaging for early detection of lung and colon cancer via ensemble deep learning model.

Scientific reports Sep 3, 2024
Cancer seems to have a vast number of deaths due to its heterogeneity, aggressiveness, and significant propensity for metastasis. The predominant categories of cancer that may affect males and females and occur worldwide are colon and lung cancer. A ...
Humans Deep Learning Neural Networks, Computer Lung Neoplasms Female Early Detection of Cancer Male Colonic Neoplasms
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Extracting lung cancer staging descriptors from pathology reports: A generative language model approach.

Journal of biomedical informatics Sep 2, 2024
BACKGROUND: In oncology, electronic health records contain textual key information for the diagnosis, staging, and treatment planning of patients with cancer. However, text data processing requires a lot of time and effort, which limits the utilizati...
Deep Learning Lung Neoplasms Natural Language Processing Neoplasm Staging Feasibility Studies Data Mining
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Integrated machine learning survival framework to decipher diverse cell death patterns for predicting prognosis in lung adenocarcinoma.

Genes and immunity Aug 31, 2024
Various forms of programmed cell death (PCD) collectively regulate the occurrence, development and metastasis of tumors. Nevertheless, a comprehensive analysis of the diverse types of PCD in lung adenocarcinoma (LUAD) is currently lacking. The study ...
Adenocarcinoma of Lung Male Humans Lung Neoplasms Cell Death Machine Learning Prognosis Female
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Deciphering Dormant Cells of Lung Adenocarcinoma: Prognostic Insights from O-glycosylation-Related Tumor Dormancy Genes Using Machine Learning.

International journal of molecular sciences Aug 31, 2024
Lung adenocarcinoma (LUAD) poses significant challenges due to its complex biological characteristics and high recurrence rate. The high recurrence rate of LUAD is closely associated with cellular dormancy, which enhances resistance to chemotherapy a...
Tumor Microenvironment Gene Expression Regulation, Neoplastic Humans Biomarkers, Tumor Glycosylation Machine Learning Gene Regulatory Networks Prognosis Adenocarcinoma of Lung Lung Neoplasms
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Application of artificial intelligence in lung cancer screening: A real-world study in a Chinese physical examination population.

Thoracic cancer Aug 29, 2024
BACKGROUND: With the rapid increase of chest computed tomography (CT) images, the workload faced by radiologists has increased dramatically. It is undeniable that the use of artificial intelligence (AI) image-assisted diagnosis system in clinical tre...
Humans China Lung Neoplasms Early Detection of Cancer East Asian People Artificial Intelligence Physical Examination Aged Tomography, X-Ray Computed Adult Female Male Middle Aged
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Artificial Intelligence Recognition Model Using Liquid-Based Cytology Images to Discriminate Malignancy and Histological Types of Non-Small-Cell Lung Cancer.

Pathobiology : journal of immunopathology, molecular and cellular biology Aug 28, 2024
INTRODUCTION: Artificial intelligence image recognition has applications in clinical practice. The purpose of this study was to develop an automated image classification model for lung cancer cytology using a deep learning convolutional neural networ...
Cytodiagnosis Image Processing, Computer-Assisted Humans Lung Neoplasms Carcinoma, Squamous Cell Neural Networks, Computer Adenocarcinoma Sensitivity and Specificity Artificial Intelligence Carcinoma, Non-Small-Cell Lung Deep Learning
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Machine Learning Based on Clinical Information and Integrated CT Radiomics to Predict Local Recurrence of Stage Ia Lung Adenocarcinoma after Microwave Ablation.

Journal of vascular and interventional radiology : JVIR Aug 28, 2024
PURPOSE: To develop and compare 3 different machine learning-based models of clinical information and integrated radiomics features predicting the local recurrence of Stage Ia lung adenocarcinoma after microwave ablation (MWA) for assisting clinical ...
Radiographic Image Interpretation, Computer-Assisted Neoplasm Recurrence, Local Microwaves Humans Margins of Excision Lung Neoplasms Middle Aged Risk Factors Machine Learning Adenocarcinoma of Lung Treatment Outcome Retrospective Studies Risk Assessment Ablation Techniques Predictive Value of Tests Decision Support Techniques Aged Tomography, X-Ray Computed Time Factors Neoplasm Staging Radiomics Clinical Decision-Making Male Female
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