Hypertension

Accelerated 3D-3D rigid registration of echocardiographic images obtained from apical window using particle filter

The perfect alignment of 3D echocardiographic images captured from various angles has improved image quality and broadened the field of view. This study proposes an accelerated sequential Monte Carlo (SMC) algorithm for 3D-3D rigid registration of transthoracic echocardiographic images with significant and limited overlap taken from apical window that is robust to the noise and intensity variati...

FineQ: Software-Hardware Co-Design for Low-Bit Fine-Grained Mixed-Precision Quantization of LLMs

Large language models (LLMs) have significantly advanced the natural language processing paradigm but impose substantial demands on memory and computational resources. Quantization is one of the most effective ways to reduce memory consumption of LLMs. However, advanced single-precision quantization methods experience significant accuracy degradation when quantizing to ultra-low bits. Existing m...

NSFlow: An End-to-End FPGA Framework with Scalable Dataflow Architecture for Neuro-Symbolic AI

Neuro-Symbolic AI (NSAI) is an emerging paradigm that integrates neural networks with symbolic reasoning to enhance the transparency, reasoning capa...

SCALE-Sim v3: A modular cycle-accurate systolic accelerator simulator for end-to-end system analysis

The rapid advancements in AI, scientific computing, and high-performance computing (HPC) have driven the need for versatile and efficient hardware a...

Low-Bit Integerization of Vision Transformers using Operand Reodering for Efficient Hardware

Pre-trained vision transformers have achieved remarkable performance across various visual tasks but suffer from expensive computational and memory ...

MedGNN: Capturing the Links Between Urban Characteristics and Medical Prescriptions

Understanding how urban socio-demographic and environmental factors relate with health is essential for public health and urban planning. However, t...

Electrocardiogram-based deep learning to predict left ventricular systolic dysfunction in paediatric and adult congenital heart disease in the USA: a multicentre modelling study.

BACKGROUND: Left ventricular systolic dysfunction (LVSD) is independently associated with cardiovascular events in patients with congenital heart dise...

Automated Bi-Ventricular Segmentation and Regional Cardiac Wall Motion Analysis for Rat Models of Pulmonary Hypertension.

Artificial intelligence-based cardiac motion mapping offers predictive insights into pulmonary hypertension (PH) disease progression and its impact on...

Integrating Large Language Models with Human Expertise for Disease Detection in Electronic Health Records

Objective: Electronic health records (EHR) are widely available to complement administrative data-based disease surveillance and healthcare performa...

Diagnosis of Pulmonary Hypertension by Integrating Multimodal Data with a Hybrid Graph Convolutional and Transformer Network

Early and accurate diagnosis of pulmonary hypertension (PH) is essential for optimal patient management. Differentiating between pre-capillary and p...

Identification of hypertension subtypes using microRNA profiles and machine learning.

OBJECTIVE: Hypertension is a major cardiovascular risk factor affecting about 1 in 3 adults. Although the majority of hypertension cases (∼90%) are cl...

Explainable AI-Guided Efficient Approximate DNN Generation for Multi-Pod Systolic Arrays

Approximate deep neural networks (AxDNNs) are promising for enhancing energy efficiency in real-world devices. One of the key contributors behind th...

CORDIC Is All You Need

Artificial intelligence necessitates adaptable hardware accelerators for efficient high-throughput million operations. We present pipelined architec...

Multimodal Lead-Specific Modeling of ECG for Low-Cost Pulmonary Hypertension Assessment

Pulmonary hypertension (PH) is frequently underdiagnosed in low- and middle-income countries (LMICs) primarily due to the scarcity of advanced diagn...

Estimating Blood Pressure with a Camera: An Exploratory Study of Ambulatory Patients with Cardiovascular Disease

Hypertension is a leading cause of morbidity and mortality worldwide. The ability to diagnose and treat hypertension in the ambulatory population is...

Artificial Intelligence-Enhanced Electrocardiography for Prediction of Incident Hypertension.

IMPORTANCE: Hypertension underpins significant global morbidity and mortality. Early lifestyle intervention and treatment are effective in reducing ad...

On Aggregation Queries over Predicted Nearest Neighbors

We introduce Aggregation Queries over Nearest Neighbors (AQNNs), a novel type of aggregation queries over the predicted neighborhood of a designated...

TabulaTime: A Novel Multimodal Deep Learning Framework for Advancing Acute Coronary Syndrome Prediction through Environmental and Clinical Data Integration

Acute Coronary Syndromes (ACS), including ST-segment elevation myocardial infarctions (STEMI) and non-ST-segment elevation myocardial infarctions (N...

A Flexible Precision Scaling Deep Neural Network Accelerator with Efficient Weight Combination

Deploying mixed-precision neural networks on edge devices is friendly to hardware resources and power consumption. To support fully mixed-precision ...

Integrating machine learning and human use experience to identify personalized pharmacotherapy in Traditional Chinese Medicine: a case study on resistant hypertension.

OBJECTIVE: To enhance the understanding of identifying personalized pharmacotherapy options in Traditional Chinese Medicine (TCM), and further support...