AIMC Journal:
Academic radiology

Showing 161 to 170 of 317 articles

Artificial Intelligence in BI-RADS Categorization of Breast Lesions on Ultrasound: Can We Omit Excessive Follow-ups and Biopsies?

Academic radiology Dec 11, 2023
RATIONALE AND OBJECTIVES: Artificial intelligence (AI) systems have been increasingly applied to breast ultrasonography. They are expected to decrease the workload of radiologists and to improve diagnostic accuracy. The aim of this study is to evalua...
Adult Sensitivity and Specificity Breast Neoplasms Middle Aged Adolescent Biopsy Ultrasonography, Mammary Female Reproducibility of Results Aged Aged, 80 and over Young Adult Humans Artificial Intelligence Retrospective Studies
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Contrast-Enhanced CT-Based Deep Learning Radiomics Nomogram for the Survival Prediction in Gallbladder Cancer.

Academic radiology Dec 6, 2023
RATIONALE AND OBJECTIVES: An accurate prognostic model is essential for the development of treatment strategies for gallbladder cancer (GBC). This study proposes an integrated model using clinical features, radiomics, and deep learning based on contr...
Adult Survival Rate Radiomics Male Middle Aged Tomography, X-Ray Computed Female Aged Aged, 80 and over Deep Learning Nomograms Contrast Media Gallbladder Neoplasms Humans Prognosis Retrospective Studies
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CEMRI-Based Quantification of Intratumoral Heterogeneity for Predicting Aggressive Characteristics of Hepatocellular Carcinoma Using Habitat Analysis: Comparison and Combination of Deep Learning.

Academic radiology Dec 6, 2023
RATIONALE AND OBJECTIVES: To explore both an intratumoral heterogeneity (ITH) model based on habitat analysis and a deep learning (DL) model based on contrast-enhanced magnetic resonance imaging (CEMRI) and validate its efficiency for predicting micr...
Retrospective Studies Female Aged Adult Male Humans Contrast Media Magnetic Resonance Imaging Neoplasm Invasiveness Predictive Value of Tests Middle Aged Deep Learning Liver Neoplasms Carcinoma, Hepatocellular
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Machine Learning Methods Based on CT Features Differentiate G1/G2 From G3 Pancreatic Neuroendocrine Tumors.

Academic radiology Dec 4, 2023
RATIONALE AND OBJECTIVES: To identify CT features for distinguishing grade 1 (G1)/grade 2 (G2) from grade 3 (G3) pancreatic neuroendocrine tumors (PNETs) using different machine learning (ML) methods.
Radiographic Image Interpretation, Computer-Assisted Machine Learning Neuroendocrine Tumors Algorithms Retrospective Studies Support Vector Machine Tomography, X-Ray Computed Diagnosis, Differential Female Pancreatic Neoplasms Aged Neoplasm Grading Adult Sensitivity and Specificity Male Middle Aged Humans
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Machine Learning Model with Computed Tomography Radiomics and Clinicobiochemical Characteristics Predict the Subtypes of Patients with Primary Aldosteronism.

Academic radiology Dec 1, 2023
RATIONALE AND OBJECTIVES: Adrenal venous sampling (AVS) is the primary method for differentiating between primary aldosterone (PA) subtypes. The aim of study is to develop prediction models for subtyping of patients with PA using computed tomography ...
Humans Machine Learning Retrospective Studies Male Middle Aged Hyperaldosteronism Aldosterone Adrenal Glands Tomography, X-Ray Computed Female Aged Adult Radiomics
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Constructing a Deep Learning Radiomics Model Based on X-ray Images and Clinical Data for Predicting and Distinguishing Acute and Chronic Osteoporotic Vertebral Fractures: A Multicenter Study.

Academic radiology Nov 27, 2023
RATIONALE AND OBJECTIVES: To construct and validate a deep learning radiomics (DLR) model based on X-ray images for predicting and distinguishing acute and chronic osteoporotic vertebral fractures (OVFs).
Nomograms Aged, 80 and over Spinal Fractures Humans Radiomics Osteoporotic Fractures Magnetic Resonance Imaging Prospective Studies Male Female Diagnosis, Differential Middle Aged Aged Chronic Disease Deep Learning Acute Disease
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Assessing the Potential of a Deep Learning Tool to Improve Fracture Detection by Radiologists and Emergency Physicians on Extremity Radiographs.

Academic radiology Nov 22, 2023
RATIONALE AND OBJECTIVES: To evaluate the standalone performance of a deep learning (DL) based fracture detection tool on extremity radiographs and assess the performance of radiologists and emergency physicians in identifying fractures of the extrem...
Sensitivity and Specificity Male Middle Aged Humans Deep Learning Aged Ohio Adolescent Retrospective Studies Child Aged, 80 and over Female Fractures, Bone Young Adult Radiologists Adult Radiographic Image Interpretation, Computer-Assisted Extremities
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Novel Deep Learning Denoising Enhances Image Quality and Lowers Radiation Exposure in Interventional Bronchial Artery Embolization Cone Beam CT.

Academic radiology Nov 21, 2023
OBJECTIVES: In interventional bronchial artery embolization (BAE), periprocedural cone beam CT (CBCT) improves guiding and localization. However, a trade-off exists between 6-second runs (high radiation dose and motion artifacts, but low noise) and 3...
Signal-To-Noise Ratio Radiography, Interventional Radiation Exposure Bronchial Arteries Cone-Beam Computed Tomography Radiographic Image Interpretation, Computer-Assisted Artifacts Embolization, Therapeutic Radiation Dosage Adult Male Middle Aged Deep Learning Humans Retrospective Studies Female Aged
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Machine Learning-Based MRI Radiogenomics for Evaluation of Response to Induction Chemotherapy in Head and Neck Squamous Cell Carcinoma.

Academic radiology Nov 18, 2023
RATIONALE AND OBJECTIVES: To develop and validate a radiogenomics model integrating clinical data, radiomics-based machine learning (RBML) classifiers, and transcriptomics data for predicting the response to induction chemotherapy (IC) in patients wi...
Humans Machine Learning Female Aged Adult Male Contrast Media Magnetic Resonance Imaging Induction Chemotherapy Imaging Genomics Middle Aged Treatment Outcome Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms
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Should All Pancreatic Cystic Lesions with Worrisome or High-Risk Features Be Resected? A Clinical and Radiological Machine Learning Model May Help to Answer.

Academic radiology Nov 17, 2023
RATIONALE AND OBJECTIVES: According to current guidelines, pancreatic cystic lesions (PCLs) with worrisome or high-risk features may have overtreatment. The purpose of this study was to build a clinical and radiological based machine-learning (ML) mo...
Pancreatic Cyst Machine Learning Retrospective Studies Tomography, X-Ray Computed Female Adult Humans Aged Sensitivity and Specificity Male Middle Aged Pancreatic Neoplasms
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