AIMC Topic: Radiomics
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Identifying severe community-acquired pneumonia using radiomics and clinical data: a machine learning approach.
Scientific reports
Sep 19, 2024
Evaluating Community-Acquired Pneumonia (CAP) is crucial for determining appropriate treatment methods. In this study, we established a machine learning model using radiomics and clinical features to rapidly and accurately identify Severe Community-A...
Can the preoperative CT-based deep learning radiomics model predict histologic grade and prognosis of chondrosarcoma?
European journal of radiology
Sep 17, 2024
BACKGROUND AND PURPOSE: Computed tomography (CT) and biopsy may be insufficient for preoperative evaluation of the grade and outcome of patients with chondrosarcoma. The aim of this study was to develop and validate a CT-based deep learning radiomics...
Deep Learning Algorithm‑Based MRI Radiomics and Pathomics for Predicting Microsatellite Instability Status in Rectal Cancer: A Multicenter Study.
Academic radiology
Sep 16, 2024
RATIONALE AND OBJECTIVES: To develop and validate multimodal deep-learning models based on clinical variables, multiparametric MRI (mp-MRI) and hematoxylin and eosin (HE) stained pathology slides for predicting microsatellite instability (MSI) status...
Intratumoral and Peritumoral Radiomics for Predicting the Prognosis of High-grade Serous Ovarian Cancer Patients Receiving Platinum-Based Chemotherapy.
Academic radiology
Sep 16, 2024
RATIONALE AND OBJECTIVES: This study aimed to develop a deep learning (DL) prognostic model to evaluate the significance of intra- and peritumoral radiomics in predicting outcomes for high-grade serous ovarian cancer (HGSOC) patients receiving platin...
An updated overview of radiomics-based artificial intelligence (AI) methods in breast cancer screening and diagnosis.
Radiological physics and technology
Sep 16, 2024
Current imaging methods for diagnosing breast cancer (BC) are associated with limited sensitivity and specificity and modest positive predictive power. The recent progress in image analysis using artificial intelligence (AI) has created great promise...
A retrospective study differentiating nontuberculous mycobacterial pulmonary disease from pulmonary tuberculosis on computed tomography using radiomics and machine learning algorithms.
Annals of medicine
Sep 16, 2024
OBJECTIVE: To evaluate the effectiveness of a machine learning based on computed tomography (CT) radiomics to distinguish nontuberculous mycobacterial pulmonary disease (NTM-PD) from pulmonary tuberculosis (PTB).
Automated classification of Alzheimer's disease, mild cognitive impairment, and cognitively normal patients using 3D convolutional neural network and radiomic features from T1-weighted brain MRI: A comparative study on detection accuracy.
Clinical imaging
Sep 16, 2024
OBJECTIVES: Alzheimer's disease (AD) is a common neurodegenerative disorder that primarily affects older individuals. Due to its high incidence, an accurate and efficient stratification system could greatly aid in the clinical diagnosis and prognosis...
Application research on the diagnosis of classic trigeminal neuralgia based on VB-Net technology and radiomics.
BMC medical imaging
Sep 16, 2024
BACKGROUND: This study aims to utilize the deep learning method of VB-Net to locate and segment the trigeminal nerve, and employ radiomics methods to distinguish between CTN patients and healthy individuals.
Multiparametric MRI-based radiomics combined with 3D deep transfer learning to predict cervical stromal invasion in patients with endometrial carcinoma.
Abdominal radiology (New York)
Sep 14, 2024
OBJECTIVE: To develop and compare various preoperative cervical stromal invasion (CSI) prediction models, including radiomics, three-dimensional (3D) deep transfer learning (DTL), and integrated models, using single-sequence and multiparametric MRI.
Adult
Radiomics
Middle Aged
Deep Learning
Humans
Retrospective Studies
Female
Aged
Neoplasm Invasiveness
Predictive Value of Tests
Image Interpretation, Computer-Assisted
Imaging, Three-Dimensional
Endometrial Neoplasms
Contrast Media
Multiparametric Magnetic Resonance Imaging
Magnetic Resonance Imaging
Cervix Uteri
Radiomics machine learning algorithm facilitates detection of small pancreatic neuroendocrine tumors on CT.
Diagnostic and interventional imaging
Sep 14, 2024
PURPOSE: The purpose of this study was to develop a radiomics-based algorithm to identify small pancreatic neuroendocrine tumors (PanNETs) on CT and evaluate its robustness across manual and automated segmentations, exploring the feasibility of autom...
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