Devices and Vaccines

MobileNetV2: A lightweight classification model for home-based sleep apnea screening

This study proposes a novel lightweight neural network model leveraging features extracted from electrocardiogram (ECG) and respiratory signals for early OSA screening. ECG signals are used to generate feature spectrograms to predict sleep stages, while respiratory signals are employed to detect sleep-related breathing abnormalities. By integrating these predictions, the method calculates the ap...

The Value of Recall in Extensive-Form Games

Imperfect-recall games, in which players may forget previously acquired information, have found many practical applications, ranging from game abstractions to team games and testing AI agents. In this paper, we quantify the utility gain by endowing a player with perfect recall, which we call the value of recall (VoR). While VoR can be unbounded in general, we parameterize it in terms of various ...

TPepRet: a deep learning model for characterizing T-cell receptors-antigen binding patterns.

MOTIVATION: T-cell receptors (TCRs) elicit and mediate the adaptive immune response by recognizing antigenic peptides, a process pivotal for cancer im...

Quantifying Public Response to COVID-19 Events: Introducing the Community Sentiment and Engagement Index

This study introduces the Community Sentiment and Engagement Index (CSEI), developed to capture nuanced public sentiment and engagement variations o...

WebLLM: A High-Performance In-Browser LLM Inference Engine

Advancements in large language models (LLMs) have unlocked remarkable capabilities. While deploying these models typically requires server-grade GPU...

Revealing the Black Box of Device Search Engine: Scanning Assets, Strategies, and Ethical Consideration

In the digital age, device search engines such as Censys and Shodan play crucial roles by scanning the internet to catalog online devices, aiding in...

Multi-concept Model Immunization through Differentiable Model Merging

Model immunization is an emerging direction that aims to mitigate the potential risk of misuse associated with open-sourced models and advancing ada...

MitraClip Device Automated Localization in 3D Transesophageal Echocardiography via Deep Learning

The MitraClip is the most widely percutaneous treatment for mitral regurgitation, typically performed under the real-time guidance of 3D transesopha...

A Unifying Information-theoretic Perspective on Evaluating Generative Models

Considering the difficulty of interpreting generative model output, there is significant current research focused on determining meaningful evaluati...

Rare Event Detection in Imbalanced Multi-Class Datasets Using an Optimal MIP-Based Ensemble Weighting Approach

To address the challenges of imbalanced multi-class datasets typically used for rare event detection in critical cyber-physical systems, we propose ...

Ultra-High-Definition Dynamic Multi-Exposure Image Fusion via Infinite Pixel Learning

With the continuous improvement of device imaging resolution, the popularity of Ultra-High-Definition (UHD) images is increasing. Unfortunately, exi...

Bayesian inference of mean velocity fields and turbulence models from flow MRI

We solve a Bayesian inverse Reynolds-averaged Navier-Stokes (RANS) problem that assimilates mean flow data by jointly reconstructing the mean flow f...

Advancing clinical trial outcomes using deep learning and predictive modelling: bridging precision medicine and patient-centered care

The integration of artificial intelligence [AI] into clinical trials has revolutionized the process of drug development and personalized medicine. A...

Risk factor identification and classification of malnutrition among under-five children in Bangladesh: Machine learning and statistical approach

This study aims to understand the factors that resulted in under-five children's malnutrition from the Multiple Indicator Cluster (MICS-2019) nation...

Utilizing Machine Learning Models to Predict Acute Kidney Injury in Septic Patients from MIMIC-III Database

Sepsis is a severe condition that causes the body to respond incorrectly to an infection. This reaction can subsequently cause organ failure, a majo...

A Miniature Batteryless Bioelectronic Implant Using One Magnetoelectric Transducer for Wireless Powering and PWM Backscatter Communication

Wireless minimally invasive bioelectronic implants enable a wide range of applications in healthcare, medicine, and scientific research. Magnetoelec...

An Integrated Approach to Develop a Potent Vaccine Candidate Construct Against Prostate Cancer by Utilizing Machine Learning and Bioinformatics.

BACKGROUND: Prostate cancer is the most common malignancy among males. Prostaglandin G/H synthase (PGHS) is an essential enzyme in the synthesis of pr...

[Discussion about Testing Scheme of Intelligent Medical Devices].

Intelligent medical devices are flourishing with the deep integration of modern information and artificial intelligence technologies into healthcare. ...

Deep Neural Network-Based Prediction of B-Cell Epitopes for SARS-CoV and SARS-CoV-2: Enhancing Vaccine Design through Machine Learning

The accurate prediction of B-cell epitopes is critical for guiding vaccine development against infectious diseases, including SARS and COVID-19. Thi...

Automatic Skull Reconstruction by Deep Learnable Symmetry Enforcement

Every year, thousands of people suffer from skull damage and require personalized implants to fill the cranial cavity. Unfortunately, the waiting ti...