Devices and Vaccines

Toward Automated Regulatory Decision-Making: Trustworthy Medical Device Risk Classification with Multimodal Transformers and Self-Training

Accurate classification of medical device risk levels is essential for regulatory oversight and clinical safety. We present a Transformer-based multimodal framework that integrates textual descriptions and visual information to predict device regulatory classification. The model incorporates a cross-attention mechanism to capture intermodal dependencies and employs a self-training strategy for i...

SacFL: Self-Adaptive Federated Continual Learning for Resource-Constrained End Devices

The proliferation of end devices has led to a distributed computing paradigm, wherein on-device machine learning models continuously process diverse data generated by these devices. The dynamic nature of this data, characterized by continuous changes or data drift, poses significant challenges for on-device models. To address this issue, continual learning (CL) is proposed, enabling machine lear...

Scaling On-Device GPU Inference for Large Generative Models

Driven by the advancements in generative AI, large machine learning models have revolutionized domains such as image processing, audio synthesis, an...

ESMpHLA: Evolutionary Scale Model-Based Deep Learning Prediction of HLA Class I Binding Peptides.

The recognition of endogenous peptides by HLA class I plays a crucial role in CD8+ T cell immune responses and human adaptive cell immune. Thus, the p...

Development of machine learning-based models for vault prediction in implantable collamer lens surgery according to implant orientation.

PURPOSE: To develop a prediction model based on machine learning to calculate the postoperative vault and the ideal implantable collamer lens (ICL) si...

Deep learning-based segmentation of the mandibular canals in cone-beam CT reaches human-level performance.

OBJECTIVES: This study evaluated the accuracy and reliability of deep learning-based segmentation techniques for mandibular canal identification in co...

Machine Learning Assisted Stroke Prediction in Mechanical Circulatory Support: Predictive Role of Systemic Mitochondrial Dysfunction.

Stroke continues to be a major adverse event in advanced congestive heart failure (CHF) patients after continuous-flow left ventricular assist device ...

Artificial Intelligence in Health Care: A Rallying Cry for Critical Clinical Research and Ethical Thinking.

Artificial intelligence (AI) will impact a large proportion of jobs in the short to medium term, especially in the developed countries. The consequenc...

Dynamic Attention Analysis for Backdoor Detection in Text-to-Image Diffusion Models

Recent studies have revealed that text-to-image diffusion models are vulnerable to backdoor attacks, where attackers implant stealthy textual trigge...

AKIBoards: A Structure-Following Multiagent System for Predicting Acute Kidney Injury

Diagnostic reasoning entails a physician's local (mental) model based on an assumed or known shared perspective (global model) to explain patient ob...

Memento: Augmenting Personalized Memory via Practical Multimodal Wearable Sensing in Visual Search and Wayfinding Navigation

Working memory involves the temporary retention of information over short periods. It is a critical cognitive function that enables humans to perfor...

Enhancing Cochlear Implant Signal Coding with Scaled Dot-Product Attention

Cochlear implants (CIs) play a vital role in restoring hearing for individuals with severe to profound sensorineural hearing loss by directly stimul...

HEMA : A Hippocampus-Inspired Extended Memory Architecture for Long-Context AI Conversations

Large language models (LLMs) struggle with maintaining coherence in extended conversations spanning hundreds of turns, despite performing well withi...

Feature Mixing Approach for Detecting Intraoperative Adverse Events in Laparoscopic Roux-en-Y Gastric Bypass Surgery

Intraoperative adverse events (IAEs), such as bleeding or thermal injury, can lead to severe postoperative complications if undetected. However, the...

3D-1D modelling of cranial plate heating induced by low or medium frequency magnetic fields

Safety assessment of patients with one-dimensionally structured passive implants, like cranial plates or stents, exposed to low or medium frequency ...

Enhancing TCR-Peptide Interaction Prediction with Pretrained Language Models and Molecular Representations

Understanding the binding specificity between T-cell receptors (TCRs) and peptide-major histocompatibility complexes (pMHCs) is central to immunothe...

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT

Integrating deep learning applications into agricultural IoT systems faces a serious challenge of balancing the high accuracy of Vision Transformers...

End-Edge Model Collaboration: Bandwidth Allocation for Data Upload and Model Transmission

The widespread adoption of large artificial intelligence (AI) models has enabled numerous applications of the Internet of Things (IoT). However, lar...

Compile Scene Graphs with Reinforcement Learning

Next-token prediction is the fundamental principle for training large language models (LLMs), and reinforcement learning (RL) further enhances their...

Compile Scene Graphs with Reinforcement Learning

Next-token prediction is the fundamental principle for training large language models (LLMs), and reinforcement learning (RL) further enhances their...