AIMC Topic: Solitary Pulmonary Nodule
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An Integrated Nomogram Combining Deep Learning and Radiomics for Predicting Malignancy of Pulmonary Nodules Using CT-Derived Nodules and Adipose Tissue: A Multicenter Study.
Cancer medicine
Nov 1, 2024
BACKGROUND: Correctly distinguishing between benign and malignant pulmonary nodules can avoid unnecessary invasive procedures. This study aimed to construct a deep learning radiomics clinical nomogram (DLRCN) for predicting malignancy of pulmonary no...
Clinical utility of an artificial intelligence radiomics-based tool for risk stratification of pulmonary nodules.
JNCI cancer spectrum
Sep 2, 2024
BACKGROUND: Clinical utility data on pulmonary nodule (PN) risk stratification biomarkers are lacking. We aimed to determine the incremental predictive value and clinical utility of using an artificial intelligence (AI) radiomics-based computer-aided...
Deep Learning-Based Reconstruction Algorithm With Lung Enhancement Filter for Chest CT: Effect on Image Quality and Ground Glass Nodule Sharpness.
Korean journal of radiology
Sep 1, 2024
OBJECTIVE: To assess the effect of a new lung enhancement filter combined with deep learning image reconstruction (DLIR) algorithm on image quality and ground-glass nodule (GGN) sharpness compared to hybrid iterative reconstruction or DLIR alone.
Assessment of Follow-Up for Pulmonary Nodules from Radiology Reports with Natural Language Processing.
Studies in health technology and informatics
Aug 22, 2024
Radiology reports are an essential communication method for ensuring smooth workflow in healthcare. However, many of these reports are described in free text, and findings documented by radiologists may not be adequately addressed. In this study, foc...
Establishment and validation of multiclassification prediction models for pulmonary nodules based on machine learning.
The clinical respiratory journal
May 1, 2024
BACKGROUND: Lung cancer is the leading cause of cancer-related death worldwide. This study aimed to establish novel multiclassification prediction models based on machine learning (ML) to predict the probability of malignancy in pulmonary nodules (PN...
Diagnostic-therapeutic management of pulmonary nodules.
Klinicka onkologie : casopis Ceske a Slovenske onkologicke spolecnosti
Jan 1, 2024
BACKGROUND: Lung cancer is one of the leading causes of death worldwide, with incidence and mortality significantly affected by population ageing and changes in the prevalence of risk factors. Lung nodules, which are often detected incidentally on im...
The effectiveness of deep learning model in differentiating benign and malignant pulmonary nodules on spiral CT.
Technology and health care : official journal of the European Society for Engineering and Medicine
Jan 1, 2024
BACKGROUND: Pulmonary nodule, one of the most common clinical phenomena, is an irregular circular lesion with a diameter of ⩽ 3 cm in the lungs, which can be classified as benign or malignant. Differentiating benign and malignant pulmonary nodules ha...
Multimodal Deep Learning Network for Differentiating Between Benign and Malignant Pulmonary Ground Glass Nodules.
Current medical imaging
Jan 1, 2024
OBJECTIVE: This study aimed to establish a multimodal deep-learning network model to enhance the diagnosis of benign and malignant pulmonary ground glass nodules (GGNs).
If Only We Had a Time Machine: Prior CT in Deep Learning for Lung Nodule Prognostication.
Radiology
Aug 1, 2023
[Deep Learning-driven Pulmonary Nodule Detection from CT Images: Challenges, Current Status and Future Directions].
Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
Feb 8, 2023
Automatic detection of pulmonary nodule based on CT images can significantly improve the diagnosis and treatment of lung cancer. Based on the characteristics of CT image and pulmonary nodule, this study summarizes the challenges and recent progresses...
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