AIMC Topic: Predictive Value of Tests
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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.
Humans
Retrospective Studies
Female
Aged
Contrast Media
Adult
Image Interpretation, Computer-Assisted
Magnetic Resonance Imaging
Radiomics
Endometrial Neoplasms
Cervix Uteri
Middle Aged
Multiparametric Magnetic Resonance Imaging
Neoplasm Invasiveness
Deep Learning
Predictive Value of Tests
Imaging, Three-Dimensional
Artificial Intelligence Algorithm Can Predict Lymph Node Malignancy from Endobronchial Ultrasound Transbronchial Needle Aspiration Images for Non-Small Cell Lung Cancer.
Respiration; international review of thoracic diseases
Sep 14, 2024
INTRODUCTION: Endobronchial ultrasound transbronchial needle aspiration (EBUS-TBNA) for lung cancer staging is operator dependent, resulting in high rates of non-diagnostic lymph node (LN) samples. We hypothesized that an artificial intelligence (AI)...
Image-based ECG analyzing deep-learning algorithm to predict biological age and mortality risks: interethnic validation.
Journal of cardiovascular medicine (Hagerstown, Md.)
Sep 12, 2024
BACKGROUND: Cardiovascular risk assessment is a critical component of healthcare, guiding preventive and therapeutic strategies. In this study, we developed and evaluated an image-based electrocardiogram (ECG) analyzing an artificial intelligence (AI...
Predictive performance of urinalysis for urine culture results according to causative microorganisms: an integrated analysis with artificial intelligence.
Journal of clinical microbiology
Sep 12, 2024
Urinary tract infections (UTIs) are pervasive and prevalent in both community and hospital settings. Recent trends in the changes of the causative microorganisms in these infections could affect the effectiveness of urinalysis (UA). We aimed to evalu...
Automated biventricular quantification in patients with repaired tetralogy of Fallot using a three-dimensional deep learning segmentation model.
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Sep 11, 2024
BACKGROUND: Deep learning is the state-of-the-art approach for automated segmentation of the left ventricle (LV) and right ventricle (RV) in cardiovascular magnetic resonance (CMR) images. However, these models have been mostly trained and validated ...
Deep Learning
Adolescent
Child
Imaging, Three-Dimensional
Treatment Outcome
Reproducibility of Results
Young Adult
Adult
Male
Ventricular Function, Left
Tetralogy of Fallot
Predictive Value of Tests
Humans
Magnetic Resonance Imaging, Cine
Cardiac Surgical Procedures
Databases, Factual
Heart Ventricles
Retrospective Studies
Ventricular Function, Right
Image Interpretation, Computer-Assisted
Female
Automation
Machine learning algorithms to predict mild cognitive impairment in older adults in China: A cross-sectional study.
Journal of affective disorders
Sep 11, 2024
OBJECTIVE: This study aimed to explore the predictive value of machine learning (ML) in mild cognitive impairment (MCI) among older adults in China and to identify important factors causing MCI.
Deep learning Radiomics Based on Two-Dimensional Ultrasound for Predicting the Efficacy of Neoadjuvant Chemotherapy in Breast Cancer.
Ultrasonic imaging
Sep 10, 2024
We investigate the predictive value of a comprehensive model based on preoperative ultrasound radiomics, deep learning, and clinical features for pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) for the breast cancer. We enro...
Prediction of poststroke independent walking using machine learning: a retrospective study.
BMC neurology
Sep 10, 2024
BACKGROUND: Accurately predicting the walking independence of stroke patients is important. Our objective was to determine and compare the performance of logistic regression (LR) and three machine learning models (eXtreme Gradient Boosting (XGBoost),...
Predicting Late Gadolinium Enhancement of Acute Myocardial Infarction in Contrast-Free Cardiac Cine MRI Using Deep Generative Learning.
Circulation. Cardiovascular imaging
Sep 10, 2024
BACKGROUND: Late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) is a standard technique for diagnosing myocardial infarction (MI), which, however, poses risks due to gadolinium contrast usage. Techniques enabling MI assessment based on...
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