Peripheral Artery Disease

Using Artificial Intelligence to Semi-Quantitate Coronary Calcium as an 'Incidentaloma' on Non-Gated, Non-Contrast CT Scans, A Single-Center Descriptive Study in West Michigan.

INTRODUCTION: Non-gated, non-contrast computed tomography (CT) scans are commonly ordered for a variety of non-cardiac indications, but do not routinely comment on the presence of coronary artery calcium (CAC)/atherosclerotic cardiovascular disease (ASCVD) which is known to correlate with increased cardiovascular risk. Artificial intelligence (AI) algorithms can help detect and quantify CAC/ASCVD ...

Cardiac Optical Coherence Tomography: History, Current Status, and Perspective.

For more than 2 decades since the first imaging procedure was performed in a living patient, intravascular optical coherence tomography (OCT), with its unprecedented image resolution, has made significant contributions to cardiovascular medicine in the realms of vascular biology research and percutaneous coronary intervention. OCT has contributed to a better understanding of vascular biology by pr...

Trapdoor endarterectomy for coral reef plaque of the paravisceral aorta in the modern era.

Coral reef atherosclerosis of the paravisceral aorta is a rare disease whose description is confined to before contemporary vascular surgical techniqu...

High-Density Lipoprotein and Heart Failure.

The protective effect of high-density lipoprotein (HDL) on atherosclerosis is well known, and its mechanisms of action has been extensively studied. H...

CT-derived pectoralis composition and incident pneumonia hospitalization using fully automated deep-learning algorithm: multi-ethnic study of atherosclerosis.

BACKGROUND: Pneumonia-related hospitalization may be associated with advanced skeletal muscle loss due to aging (i.e., sarcopenia) or chronic illnesse...

Automated Segmentation and Classification of Knee Synovitis Based on MRI Using Deep Learning.

OBJECTIVES: To develop a deep learning (DL) model for segmentation of the suprapatellar capsule (SC) and infrapatellar fat pad (IPFP) based on sagitta...

Correlation Between Statin Use and Symptomatic Venous Thromboembolism Incidence in Patients With Ankle Fracture: A Machine Learning Approach.

BACKGROUND: Identifying factors that correlate with the incidence of venous thromboembolism (VTE) has the potential to improve VTE prevention and posi...

Improving cardiovascular risk prediction through machine learning modelling of irregularly repeated electronic health records.

AIMS: Existing electronic health records (EHRs) often consist of abundant but irregular longitudinal measurements of risk factors. In this study, we a...

Ethical Considerations in Neuroprognostication Following Acute Brain Injury.

Neuroprognostication following acute brain injury (ABI) is a complex process that involves integrating vast amounts of information to predict a patien...

Ultra-fast ultrasound blood flow velocimetry for carotid artery with deep learning.

Accurate measurement of blood flow velocity is important for the prevention and early diagnosis of atherosclerosis. However, due to the uncertainty of...

Elderly Patients' Outcomes After Robot-Assisted Radical Prostatectomy: A Single Center Experience.

To assess the oncological and functional outcomes of patients aged 70 years or older after robot-assisted radical prostatectomy (RARP) and compare th...

Role of puboperinealis and rectourethralis muscles as a urethral support system to maintain urinary continence after robot-assisted radical prostatectomy.

The present study investigated the role of a urethral support system to maintain urinary continence after robot-assisted radical prostatectomy (RARP),...

Metadata and Image Features Co-Aware Personalized Federated Learning for Smart Healthcare.

Recently, artificial intelligence has been widely used in intelligent disease diagnosis and has achieved great success. However, most of the works mai...

Urinary continence recovery after Retzius-sparing robot-assisted radical prostatectomy in relation to surgeon experience.

Urinary incontinence is one of the main concerns for patients after radical prostatectomy. Differences in surgical experience among surgeons could par...

Comparing the performance of machine learning and conventional models for predicting atherosclerotic cardiovascular disease in a general Chinese population.

BACKGROUND: Accurately predicting the risk of atherosclerotic cardiovascular disease (ASCVD) is crucial for implementing individualized prevention str...

A Dataset Auditing Method for Collaboratively Trained Machine Learning Models.

Dataset auditing for machine learning (ML) models is a method to evaluate if a given dataset is used in training a model. In a Federated Learning sett...

Impact of modified bladder neck suspension on early recovery of continence after robot-assisted radical prostatectomy (RARP).

The incontinence after RARP significantly decreases the quality of life in prostate cancer patients. A number of techniques have been introduced for t...

Robust Detection, Segmentation, and Metrology of High Bandwidth Memory 3D Scans Using an Improved Semi-Supervised Deep Learning Approach.

Recent advancements in 3D deep learning have led to significant progress in improving accuracy and reducing processing time, with applications spannin...

Classification of health deterioration by geometric invariants.

BACKGROUND AND OBJECTIVES: Prediction of patient deterioration is essential in medical care, and its automation may reduce the risk of patient death. ...

AI-Driven sleep staging from actigraphy and heart rate.

Sleep is an important indicator of a person's health, and its accurate and cost-effective quantification is of great value in healthcare. The gold sta...