Cardiovascular

Strokes

Latest AI and machine learning research in strokes for healthcare professionals.

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Artificial-intelligence-based risk prediction and mechanism discovery for atrial fibrillation using heart beat-to-beat intervals.

BACKGROUND: Early diagnosis of atrial fibrillation (AF) is important for preventing stroke and other...

Effects of thienopyridine class antiplatelets on bleeding outcomes following robot-assisted radical prostatectomy.

This study aimed to assess the effects of thienopyridine-class antiplatelet agents (including ticlop...

Sensor-Based Measurement Method to Support the Assessment of Robot-Assisted Radiofrequency Ablation.

Digital surgery technologies, such as interventional robotics and sensor systems, not only improve p...

Uncertainty-aware deep learning for trustworthy prediction of long-term outcome after endovascular thrombectomy.

Acute ischemic stroke (AIS) is a leading global cause of mortality and morbidity. Improving long-ter...

Magnetic resonance imaging-based deep learning imaging biomarker for predicting functional outcomes after acute ischemic stroke.

PURPOSE: Clinical risk scores are essential for predicting outcomes in stroke patients. The advancem...

Utilizing imaging parameters for functional outcome prediction in acute ischemic stroke: A machine learning study.

BACKGROUND AND PURPOSE: We aimed to predict the functional outcome of acute ischemic stroke patients...

Data Augmentation Techniques for Accurate Action Classification in Stroke Patients with Hemiparesis.

Stroke survivors with hemiparesis require extensive home-based rehabilitation. Deep learning-based c...

Artificial intelligence-based model for predicting pulmonary arterial hypertension on chest x-ray images.

BACKGROUND: Pulmonary arterial hypertension is a serious medical condition. However, the condition i...

Deep Learning based Retinal Vessel Caliber Measurement and the Association with Hypertension.

PURPOSE: To develop a highly efficient and fully automated method that measures retinal vessel calib...

Trends in stroke-related journals: Examination of publication patterns using topic modeling.

OBJECTIVES: This study aims to demonstrate the capacity of natural language processing and topic mod...

Dietary patterns associated with the incidence of hypertension among adult Japanese males: application of machine learning to a cohort study.

PURPOSE: The previous studies that examined the effectiveness of unsupervised machine learning metho...

Simultaneous high-definition transcranial direct current stimulation and robot-assisted gait training in stroke patients.

This study investigates whether simultaneous high-definition transcranial direct current stimulation...

A stroke prediction framework using explainable ensemble learning.

The death of brain cells occurs when blood flow to a particular area of the brain is abruptly cut of...

The importance of data in Pulmonary Arterial Hypertension: from international registries to Machine Learning.

Real-world registries have been critical to building the scientific knowledge of rare diseases, incl...

Machine learning decision support model for discharge planning in stroke patients.

BACKGROUND/AIM: Efficient discharge for stroke patients is crucial but challenging. The study aimed ...

Convolutional neuronal network for identifying single-cell-platelet-platelet-aggregates in human whole blood using imaging flow cytometry.

Imaging flow cytometry is an attractive method to investigate individual cells by optical properties...

Assessing the clinical reasoning of ChatGPT for mechanical thrombectomy in patients with stroke.

BACKGROUND: Artificial intelligence (AI) has become a promising tool in medicine. ChatGPT, a large l...

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