Osteoporosis

Classifying Pseudogout Using Machine Learning Approaches With Electronic Health Record Data.

OBJECTIVE: Identifying pseudogout in large data sets is difficult due to its episodic nature and a lack of billing codes specific to this acute subtype of calcium pyrophosphate (CPP) deposition disease. The objective of this study was to evaluate a novel machine learning approach for classifying pseudogout using electronic health record (EHR) data.

Opportunistic Screening at Abdominal CT: Use of Automated Body Composition Biomarkers for Added Cardiometabolic Value.

Abdominal CT is a frequently performed imaging examination for a wide variety of clinical indications. In addition to the immediate reason for scanning, each CT examination contains robust additional data on body composition that generally go unused in routine clinical practice. There is now growing interest in harnessing this additional information. Prime examples of cardiometabolic information i...

Surgical management of secondary hyperparathyroidism in dialysis patients in Senegal.

Secondary hyperparathyroidism (SHPT) is a common complication of end-stage renal disease. Surgical management occurs in severe forms and/or unresponsi...

Machine learning to predict the long-term risk of myocardial infarction and cardiac death based on clinical risk, coronary calcium, and epicardial adipose tissue: a prospective study.

AIMS: Our aim was to evaluate the performance of machine learning (ML), integrating clinical parameters with coronary artery calcium (CAC), and automa...

[Artificial intelligence-based algorithms : Decision-making support for computed tomography of the chest].

Artificial intelligence (AI) algorithms are increasingly used in radiology. The main areas of application are, for example, the detection of lung lesi...

[A comparative study on treatment of lumbar degenerative disease with osteoporosis by manual and robot-assisted cortical bone trajectory screws fixation].

OBJECTIVE: To compare the safety and accuracy of manual and robot-assisted cortical bone trajectory (CBT) screws fixation in the treatment of lumbar d...

Accuracy of an Artificial Intelligence Deep Learning Algorithm Implementing a Recurrent Neural Network With Long Short-term Memory for the Automated Detection of Calcified Plaques From Coronary Computed Tomography Angiography.

PURPOSE: The purpose of this study was to evaluate the accuracy of a novel fully automated deep learning (DL) algorithm implementing a recurrent neura...

Machine Learning and Deep Neural Networks Applications in Computed Tomography for Coronary Artery Disease and Myocardial Perfusion.

During the latest years, artificial intelligence, and especially machine learning (ML), have experienced a growth in popularity due to their versatili...

Machine learning of clinical variables and coronary artery calcium scoring for the prediction of obstructive coronary artery disease on coronary computed tomography angiography: analysis from the CONFIRM registry.

AIMS: Symptom-based pretest probability scores that estimate the likelihood of obstructive coronary artery disease (CAD) in stable chest pain have mod...

Application and Development of Artificial Intelligence and Intelligent Disease Diagnosis.

With the continuous development of artificial intelligence (AI) technology, big data-supported AI technology with considerable computer and learning c...

Diagnosis of Osteoporosis using modified U-net architecture with attention unit in DEXA and X-ray images.

BACKGROUND: Osteoporosis, a silent killing disease of fracture risk, is normally determined based on the bone mineral density (BMD) and T-score values...

Complete Molar Pregnancy in Posmenopausal Woman-a Case Report.

INTRODUCTION: Gestational trophoblastic desease (GTD) is disease typical for reproductive period of women and is extremly rare in postmenopausal perio...

20th Annual Feigenbaum Lecture: Echocardiography for Precision Medicine-Digital Biopsy to Deconstruct Biology.

Heart failure with preserved ejection fraction (HFpEF) is a complex, heterogeneous syndrome in need of improved classification given its high morbidit...

Ex-vivo antihypertensive and calcium channel blocking activity of Androsace foliosa n-hexane leaves fraction on isolated rabbit aorta.

Hypertension is persistent elevation in blood pressure for 3-4 weeks. Estimated global prevalence of hypertension suggested that by the Year 2025 (29%...

Sarcopenia feature selection and risk prediction using machine learning: A cross-sectional study.

The purpose of this study was to verify the usefulness of machine learning (ML) for selection of risk factors and development of predictive models for...

Automated segmentation and quantification of aortic calcification at abdominal CT: application of a deep learning-based algorithm to a longitudinal screening cohort.

OBJECTIVE: To investigate an automated aortic calcium segmentation and scoring tool at abdominal CT in an adult screening cohort.

Artificial intelligence, osteoporosis and fragility fractures.

PURPOSE OF REVIEW: Artificial intelligence tools have found new applications in medical diagnosis. These tools have the potential to capture underlyin...

Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging.

Artificial intelligence (AI) has transformed key aspects of human life. Machine learning (ML), which is a subset of AI wherein machines autonomously a...

Cardiovascular calcification: artificial intelligence and big data accelerate mechanistic discovery.

Cardiovascular calcification is a health disorder with increasing prevalence and high morbidity and mortality. The only available therapeutic options ...

Physical Activity Change in an RCT: Comparison of Measurement Methods.

We aimed to quantify the agreement between self-report, standard cut-point accelerometer, and machine learning accelerometer estimates of physical ac...