AIMC Topic: Calcinosis
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Development and external validation of a machine learning model for cardiac valve calcification early screening in dialysis patients: a multicenter study.
Renal failure
Apr 24, 2025
BACKGROUND: Cardiac valve calcification (CVC) is common in dialysis patients and associated with increased cardiovascular risk. However, early screening has been limited by cost concerns. This study aimed to develop and validate a machine learning mo...
Deep learning based automatic quantification of aortic valve calcification on contrast enhanced coronary CT angiography.
Scientific reports
Mar 12, 2025
Quantifying aortic valve calcification is critical for assessing the severity of aortic stenosis, predicting cardiovascular risk, and guiding treatment decisions. This study evaluated the feasibility of a deep learning-based automatic quantification ...
Segmentation of coronary artery and calcification using prior knowledge based deep learning framework.
Medical physics
Jan 29, 2025
BACKGROUND: Computed tomography angiography (CTA) is used to screen for coronary artery calcification. As the coronary artery has complicated structure and tiny lumen, manual screening is a time-consuming task. Recently, many deep learning methods ha...
Negative prognostic factors and clinical improvement prediction modeling for extracorporeal shockwave therapy in calcific shoulder tendinitis using artificial intelligence techniques.
Journal of shoulder and elbow surgery
Jan 19, 2025
BACKGROUND: The efficacy of extracorporeal shockwave therapy (ESWT) for treating shoulder calcific tendinitis can be influenced by various prognostic factors. This study aimed to identify prognostic factors associated with the failure of ESWT for sym...
Identification and validation of the diagnostic biomarker MFAP5 for CAVD with type 2 diabetes by bioinformatics analysis.
Frontiers in immunology
Dec 19, 2024
INTRODUCTION: Calcific aortic valve disease (CAVD) is increasingly prevalent among the aging population, and there is a notable lack of drug therapies. Consequently, identifying novel drug targets will be of utmost importance. Given that type 2 diabe...
Artificial Intelligence-Assisted Segmentation of a Falx Cerebri Calcification on Cone-Beam Computed Tomography: A Case Report.
Medicina (Kaunas, Lithuania)
Dec 12, 2024
Intracranial calcifications, particularly within the falx cerebri, serve as crucial diagnostic markers ranging from benign accumulations to signs of severe pathologies. The falx cerebri, a dural fold that separates the cerebral hemispheres, presents ...
Deep Learning Model of Diastolic Dysfunction Risk Stratifies the Progression of Early-Stage Aortic Stenosis.
JACC. Cardiovascular imaging
Sep 18, 2024
BACKGROUND: The development and progression of aortic stenosis (AS) from aortic valve (AV) sclerosis is highly variable and difficult to predict.
Ventricular Dysfunction, Left
Diastole
Sclerosis
Calcinosis
Echocardiography
Middle Aged
Aortic Valve Stenosis
Risk Factors
Risk Assessment
Aortic Valve
Aged
Severity of Illness Index
Disease Progression
Humans
Predictive Value of Tests
Male
Deep Learning
Prognosis
Ventricular Function, Left
Female
Time Factors
Reproducibility of Results
United States
Deep transfer learning for detection of breast arterial calcifications on mammograms: a comparative study.
European radiology experimental
Jul 15, 2024
INTRODUCTION: Breast arterial calcifications (BAC) are common incidental findings on routine mammograms, which have been suggested as a sex-specific biomarker of cardiovascular disease (CVD) risk. Previous work showed the efficacy of a pretrained con...
Deep-learning survival analysis for patients with calcific aortic valve disease undergoing valve replacement.
Scientific reports
May 13, 2024
Calcification of the aortic valve (CAVDS) is a major cause of aortic stenosis (AS) leading to loss of valve function which requires the substitution by surgical aortic valve replacement (SAVR) or transcatheter aortic valve intervention (TAVI). These ...
MOB-CBAM: A dual-channel attention-based deep learning generalizable model for breast cancer molecular subtypes prediction using mammograms.
Computer methods and programs in biomedicine
Mar 10, 2024
BACKGROUND AND OBJECTIVE: Deep Learning models have emerged as a significant tool in generating efficient solutions for complex problems including cancer detection, as they can analyze large amounts of data with high efficiency and performance. Recen...
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