Devices and Vaccines

Reliable stability prediction to manage research or marketed vaccines and pharmaceutical products. "Avoid any doubt for the end-user of vaccine compliance at time of administration".

A major challenge for the pharmaceutical/vaccine industry is to anticipate and test/control product stability, regardless of the time/temperature profile of the product, from release to administration. Current empirical stability protocols performed to ensure product stability remain limited to the prediction of product stability in a thermal excursion (cold chain break) during their long-term sto...

Compressed Deep Learning to Classify Arrhythmia in an Embedded Wearable Device.

The importance of an embedded wearable device with automatic detection and alarming cannot be overstated, given that 15-30% of patients with atrial fibrillation are reported to be asymptomatic. These asymptomatic patients do not seek medical care, hence traditional diagnostic tools including Holter are not effective for the further prevention of associated stroke or heart failure. This is likely t...

Progress and Challenges for Memtransistors in Neuromorphic Circuits and Systems.

Due to the increasing importance of artificial intelligence (AI), significant recent effort has been devoted to the development of neuromorphic circui...

Three-dimensional deep learning to automatically generate cranial implant geometry.

We present a 3D deep learning framework that can generate a complete cranial model using a defective one. The Boolean subtraction between these two mo...

Development of a code-free machine learning model for the classification of cataract surgery phases.

This study assessed the performance of automated machine learning (AutoML) in classifying cataract surgery phases from surgical videos. Two ophthalmol...

Is Artificial Intelligence (AI) a Pipe Dream? Why Legal Issues Present Significant Hurdles to AI Autonomy.

Proponents of artificial intelligence (AI) technology have suggested that in the near future, AI software may replace human radiologists. Although ass...

The Ability of Deep Learning Models to Identify Total Hip and Knee Arthroplasty Implant Design From Plain Radiographs.

INTRODUCTION: The surgical management of patients with failed total hip or knee arthroplasty (THA and TKA) necessitates the identification of the impl...

Analyzing the Effect of Vaccination Over COVID Cases and Deaths in Asian Countries Using Machine Learning Models.

Coronavirus Disease 2019 (COVID-19) is spreading across the world, and vaccinations are running parallel. Coronavirus has mutated into a triple-mutate...

Enabling CT-Scans for covid detection using transfer learning-based neural networks.

Today, we are coping with the pandemic, and the novel virus is covertly evolving day by day. Therefore, a precautionary system to deal with the issue ...

Developing Affordable, Portable and Simplistic Diagnostic Sensors to Improve Access to Care.

Ophthalmology is a highly technical specialty, especially in the area of diagnostic equipment. While the field is innovative, the access to cutting-ed...

A Cylindrical Grip Type of Tactile Device Using Magneto-Responsive Materials Integrated with Surgical Robot Console: Design and Analysis.

This paper proposes a cylindrical grip type of tactile device that is effectively integrated to a surgical robot console so that a surgeon can easily ...

Low-radiation dose scan protocol for preoperative imaging for dental implant surgery using deep learning-based reconstruction in multidetector CT.

OBJECTIVES: This study aimed to investigate the impact of a deep learning-based reconstruction (DLR) technique on image quality and reduction of radia...

A Graph Neural Network Based Decentralized Learning Scheme.

As an emerging paradigm considering data privacy and transmission efficiency, decentralized learning aims to acquire a global model using the training...

Stretchable Neuromorphic Transistor That Combines Multisensing and Information Processing for Epidermal Gesture Recognition.

We fabricated a nanowire-channel intrinsically stretchable neuromorphic transistor (NISNT) that perceives both tactile and visual information and emul...

Performance change with the number of training data: A case study on the binary classification of COVID-19 chest X-ray by using convolutional neural networks.

One of the features of artificial intelligence/machine learning-based medical devices resides in their ability to learn from real-world data. However,...

COVID-19 detection in CT and CXR images using deep learning models.

Infectious diseases pose a threat to human life and could affect the whole world in a very short time. Corona-2019 virus disease (COVID-19) is an exam...

A Knowledge Distillation Ensemble Framework for Predicting Short- and Long-Term Hospitalization Outcomes From Electronic Health Records Data.

The ability to perform accurate prognosis is crucial for proactive clinical decision making, informed resource management and personalised care. Exist...

Automated selection of mid-height intervertebral disc slice in traverse lumbar spine MRI using a combination of deep learning feature and machine learning classifier.

Abnormalities and defects that can cause lumbar spinal stenosis often occur in the Intervertebral Disc (IVD) of the patient's lumbar spine. Their auto...

Artificial intelligence predicts clinically relevant atrial high-rate episodes in patients with cardiac implantable electronic devices.

To assess the utility of machine learning (ML) algorithms in predicting clinically relevant atrial high-rate episodes (AHREs), which can be recorded b...

A Remote Calibration Device Using Edge Intelligence.

Power system facility calibration is a compulsory task that requires in-site operations. In this work, we propose a remote calibration device that inc...