Devices and Vaccines

Analog Bayesian neural networks are insensitive to the shape of the weight distribution

Recent work has demonstrated that Bayesian neural networks (BNN's) trained with mean field variational inference (MFVI) can be implemented in analog hardware, promising orders of magnitude energy savings compared to the standard digital implementations. However, while Gaussians are typically used as the variational distribution in MFVI, it is difficult to precisely control the shape of the noise...

Quantifying Itch and its Impact on Sleep Using Machine Learning and Radio Signals

Chronic itch affects 13% of the US population, is highly debilitating, and underlies many medical conditions. A major challenge in clinical care and new therapeutics development is the lack of an objective measure for quantifying itch, leading to reliance on subjective measures like patients' self-assessment of itch severity. In this paper, we show that a home radio device paired with artificial...

ElasticZO: A Memory-Efficient On-Device Learning with Combined Zeroth- and First-Order Optimization

Zeroth-order (ZO) optimization is being recognized as a simple yet powerful alternative to standard backpropagation (BP)-based training. Notably, ZO...

Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding

Background: Healthcare has many manual processes that can benefit from automation and augmentation with Generative Artificial Intelligence (AI), the...

Simulated prosthetic vision confirms checkerboard as an effective raster pattern for epiretinal implants

Spatial scheduling of electrode activation ("rastering") is essential for safely operating high-density retinal implants, yet its perceptual consequ...

Spatiotemporal Abstraction Theory: Re‐Interpretation of Localized Cortical Networks

The brain excels at extracting meaning from noisy and degraded input, yet the computational principles that underlie this robustness remain unclear. W...

Language models learn to represent antigenic properties of human influenza A(H3) virus

Given that influenza vaccine effectiveness depends on a good antigenic match between the vaccine and circulating viruses, it is important to assess th...

Pixel-Precise Lesion Localization in WSIs via Weakly Supervised Streaming Convolution with ReLSE and Adaptive Self-Training

A robust artificial intelligence-assisted workflow for tumor assessment in pathology requires not only accurate classification but also precise lesion...

Controllable Protein Design by Prefix-Tuning Protein Language Models

The design of novel proteins with tailored functionalities, particularly in drug discovery and vaccine development, presents a transformative approach...

Optimization of connectome weights for a neural network model generating both forward and backward locomotion in C. elegans

Previous studies tracking the relationship between manipulations of C. elegans neurons and the resulting behavioral changes have called for the develo...

CoV-UniBind: A Unified Antibody Binding Database for SARS-CoV-2

Since the emergence of SARS-CoV-2, numerous studies have investigated antibody interactions with viral variants in vitro, and several datasets have be...

Quantum Convolutional HLA Immunogenic Peptide Prediction (Q-CHIPP): Next-Generation Neoantigen Prediction with Quantum Neural Networks

The immune system is an intricately evolved series of cellular and protein-protein interactions, which defend the body against pathogens and abnormal ...

Tension shapes memory: Computational insights into neural plasticity

Mechanical forces have recently emerged as critical modulators of neural communication, yet their role in high-level cognitive functions remains poorl...

Mapping antigenic evolution of influenza A virus using deep learning-based prediction of hemagglutination inhibition titers

Seasonal influenza remains a significant public health challenge through unpredictable antigenic drift, where accumulated mutations enable immune evas...

Reengineering the antigen optimization process for superior neoantigen vaccine design

Identifying effective neoantigen sequences is essential for enhancing anti-tumor immunity. However, the vast sequence space (>109 possible peptides) a...

From sequence to scaffold: computational design of protein nanoparticle vaccines from AlphaFold2-predicted building blocks

Self-assembling protein nanoparticles are being increasingly utilized in the design of next-generation vaccines due to their ability to induce antibod...

APDeeM: A machine Learning strategy towards Effective Peptide Vaccine Candidates Identification against Different Types of Viruses

Viral infections pose significant global health challenges, underscoring the urgent need for improved medications. Nevertheless, traditional medicinal...

The development of FEDUPP: Feeding Experimentation Device Users Processing Package to Assess Learning and Cognitive Flexibility

Cognitive flexibility, the ability to adapt behavior in response to changing contingencies, is a key component of adaptive decision-making and is impa...

BLMPred: predicting linear B-cell epitopes using pre-trained protein language models and machine learning

B-cells get activated through interaction with B-cell epitopes, a specific portion of the antigen. Identification of B-cell epitopes is crucial for a ...

Natural language processing captures memory content associated with shared neural patterns at encoding

People can experience the same event yet form distinct memories shaped by individual interpretations. Prior research shows that multivariate activity ...