AIMC Topic: Sensitivity and Specificity
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The value of multiparametric MRI radiomics and machine learning in predicting preoperative Ki-67 expression level in breast cancer.
BMC medical imaging
Jan 7, 2025
OBJECTIVE: This study was to develop a multi-parametric MRI radiomics model to predict preoperative Ki-67 status.
Plasma Epstein-Barr Virus DNA load for diagnostic and prognostic assessment in intestinal Epstein-Barr Virus infection.
Frontiers in cellular and infection microbiology
Jan 7, 2025
BACKGROUND: The prospective application of plasma Epstein-Barr virus (EBV) DNA load as a noninvasive measure of intestinal EBV infection remains unexplored. This study aims to identify ideal threshold levels for plasma EBV DNA loads in the diagnosis ...
Open-source Large Language Models can Generate Labels from Radiology Reports for Training Convolutional Neural Networks.
Academic radiology
Jan 6, 2025
RATIONALE AND OBJECTIVES: Training Convolutional Neural Networks (CNN) requires large datasets with labeled data, which can be very labor-intensive to prepare. Radiology reports contain a lot of potentially useful information for such tasks. However,...
High performance COVID-19 screening using machine learning.
La Tunisie medicale
Jan 5, 2025
Since the World Health Organization declared the Coronavirus Disease 2019 (COVID-19) pandemic as an international concern of public health emergency in the early 2020, several strategies have been initiated in many countries to prevent healthcare ser...
Automated ultrasonography of hepatocellular carcinoma using discrete wavelet transform based deep-learning neural network.
Medical image analysis
Jan 4, 2025
This study introduces HCC-Net, a novel wavelet-based approach for the accurate diagnosis of hepatocellular carcinoma (HCC) from abdominal ultrasound (US) images using artificial neural networks. The HCC-Net integrates the discrete wavelet transform (...
Neural Network and Logistic Regression Models Based on Ultrasound Radiomics and Clinical-Pathological Features to Predict Occult Level II Lymph Node Metastasis in Papillary Thyroid Carcinoma.
Academic radiology
Jan 4, 2025
RATIONALE AND OBJECTIVES: Papillary thyroid carcinoma (PTC) often metastasizes to lateral cervical lymph nodes, especially in level II. This study aims to develop predictive models to identify level II lymph node metastasis (LNM), guiding selective n...
Dual-Stage AI Model for Enhanced CT Imaging: Precision Segmentation of Kidney and Tumors.
Tomography (Ann Arbor, Mich.)
Jan 3, 2025
OBJECTIVES: Accurate kidney and tumor segmentation of computed tomography (CT) scans is vital for diagnosis and treatment, but manual methods are time-consuming and inconsistent, highlighting the value of AI automation. This study develops a fully au...
An Automatic Deep-Radiomics Framework for Prostate Cancer Diagnosis and Stratification in Patients with Serum Prostate-Specific Antigen of 4.0-10.0 ng/mL: A Multicenter Retrospective Study.
Academic radiology
Jan 2, 2025
RATIONALE AND OBJECTIVES: To develop an automatic deep-radiomics framework that diagnoses and stratifies prostate cancer in patients with prostate-specific antigen (PSA) levels between 4 and 10 ng/mL.
Performance analysis of a deep-learning algorithm to detect the presence of inflammation in MRI of sacroiliac joints in patients with axial spondyloarthritis.
Annals of the rheumatic diseases
Jan 2, 2025
OBJECTIVES: To assess the ability of a previously trained deep-learning algorithm to identify the presence of inflammation on MRI of sacroiliac joints (SIJ) in a large external validation set of patients with axial spondyloarthritis (axSpA).
International multicenter validation of AI-driven ultrasound detection of ovarian cancer.
Nature medicine
Jan 2, 2025
Ovarian lesions are common and often incidentally detected. A critical shortage of expert ultrasound examiners has raised concerns of unnecessary interventions and delayed cancer diagnoses. Deep learning has shown promising results in the detection o...
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