Latest AI and machine learning research in devices and vaccines for healthcare professionals.
Machine learning (ML) classifiers serve as essential tools facilitating classification and prediction across various domains. The performance of these algorithms should be known to ensure their reliable application. In certain fields, receiver operating characteristic and precision-recall curves are frequently employed to assess machine learning algorithms without accounting for the impact of pr...
This paper presents a memristor-based compute-in-memory hardware accelerator for on-chip training and inference, focusing on its accuracy and efficiency against device variations, conductance errors, and input noise. Utilizing realistic SPICE models of commercially available silver-based metal self-directed channel (M-SDC) memristors, the study incorporates inherent device non-idealities into th...
Electronic health data concerning implantable medical devices (IMD) opens opportunities for dynamic real-world monitoring to assess associated risks r...
Introduction: Electrical impedance spectroscopy (EIS) has recently developed as a novel diagnostic device for screening and evaluating cervical dysp...
Mobile devices, especially smartphones, can support rich functions and have developed into indispensable tools in daily life. With the rise of gener...
Convolutional Neural Networks (CNNs) have received substantial attention as a highly effective tool for analyzing medical images, notably in interpret...
Edge computing is a distributed computing paradigm that collects and processes data at or near the source of data generation. The on-device learning...
OBJECTIVES: To investigate the usefulness of super-resolution deep learning reconstruction (SR-DLR) with cardiac option in the assessment of image qua...
HYPOTHESIS: Here, we aim to 1) expand the available evidence for the use of machine learning techniques for soft tissue classification after BCD surge...
BACKGROUND: Stent malapposition (SM) following percutaneous coronary intervention (PCI) for myocardial infarction continues to present significant cli...
Large amounts of important medical information are captured in free-text documents in biomedical research and within healthcare systems, which can be ...
Integrating cameras into wireless smart rings has been challenging due to size and power constraints. We introduce IRIS, the first wireless vision-e...
In clinical treatment, identifying potential adverse reactions of drugs can help assist doctors in making medication decisions. In response to the p...
A vaccine passport serves as documentary proof, providing passport holders with greater freedom while roaming around during pandemics. It confirms v...
Liver zonation is a fundamental characteristic of hepatocyte spatial heterogeneity, which is challenging to recapitulate in traditional cell culture...
Purpose: Federated training is often hindered by heterogeneous datasets due to divergent data storage options, inconsistent naming schemes, varied a...
On-device inference holds great potential for increased energy efficiency, responsiveness, and privacy in edge ML systems. However, due to less capa...
In this paper, we address a recent trend in robotic home appliances to include vision systems on personal devices, capable of personalizing the appl...
This demo presents a novel end-to-end framework that combines on-device large language models (LLMs) with smartphone sensing technologies to achieve...
With the rapid advances in deep learning and smart manufacturing in Industry 4.0, there is an imperative for high-throughput, high-performance, and ...