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Devices and Vaccines

Latest AI and machine learning research in devices and vaccines for healthcare professionals.

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Showing 1576-1596 of 4,651 articles
MADE: A Living Benchmark for Multi-Label Text Classification with Uncertainty Quantification of Medical Device Adverse Events

Machine learning in high-stakes domains such as healthcare requires not only strong predictive perfo...

Mitigating S-RAHA: An On-device Framework to Prevent Forwarding of Re-Captured Images

Protecting sensitive visual content from unauthorized redistribution is a growing challenge for priv...

A Compact and Efficient 1.251 Million Parameter Machine Learning CNN Model PD36-C for Plant Disease Detection: A Case Study

Deep learning has markedly advanced image based plant disease diagnosis as improved hardware and dat...

Immune2V: Image Immunization Against Dual-Stream Image-to-Video Generation

Image-to-video (I2V) generation has the potential for societal harm because it enables the unauthori...

Using Synthetic Data for Machine Learning-based Childhood Vaccination Prediction in Narok, Kenya

Background: Limited data utilization in low-resource settings poses a barrier to the vaccine deliver...

CLIP-Inspector: Model-Level Backdoor Detection for Prompt-Tuned CLIP via OOD Trigger Inversion

Organisations with limited data and computational resources increasingly outsource model training to...

Rapidly deploying on-device eye tracking by distilling visual foundation models

Eye tracking (ET) plays a critical role in augmented and virtual reality applications. However, rapi...

LiteInception: A Lightweight and Interpretable Deep Learning Framework for General Aviation Fault Diagnosis

General aviation fault diagnosis and efficient maintenance are critical to flight safety; however, d...

Predicting long-term adverse outcomes after neonatal intensive care

Neonates requiring intensive care are at increased risk for long-term neuropsychiatric disorders. Ho...

DreamLite: A Lightweight On-Device Unified Model for Image Generation and Editing

Diffusion models have made significant progress in both text-to-image (T2I) generation and text-guid...

An Energy-Efficient Spiking Neural Network Architecture for Predictive Insulin Delivery

Diabetes mellitus affects over 537 million adults worldwide. Insulin-dependent patients require cont...

ROAST: Risk-aware Outlier-exposure for Adversarial Selective Training of Anomaly Detectors Against Evasion Attacks

Safety-critical domains like healthcare rely on deep neural networks (DNNs) for prediction, yet DNNs...

Predicting Infant Nonattendance at the Next Recommended Well-Child Visit: Model Development and Validation

BackgroundWell-child visits (WCVs) are essential for preventive care, yet missed appointments often ...

Associative Memory using Attribute-Specific Neuron Groups-2: Learning and Sequential Associative Recall between Cue Neurons for different Cue Balls

This paper introduces a neural network model that learns multiple attributes as images and performs ...

CIAR: Interval-based Collaborative Decoding for Image Generation Acceleration

Auto-regressive (AR) models have recently made notable progress in image generation, achieving perfo...

RNASTOP: A Deep Learning Framework for mRNA Chemical Stability Prediction and Optimization

Messenger RNA (mRNA) vaccines offer promising therapeutics for combating various diseases, yet their...

STEP: Detecting Audio Backdoor Attacks via Stability-based Trigger Exposure Profiling

With the widespread deployment of deep-learning-based speech models in security-critical application...

Context-Aware Emergency Department Triage Using Pairwise Comparisons and Bradley-Terry Aggregation

Objective: To evaluate a ranking approach for emergency department (ED) waiting room prioritization ...

Prompting with the human-touch: evaluating model-sensitivity of foundation models for musculoskeletal CT segmentation

Promptable Foundation Models (FMs), initially introduced for natural image segmentation, have also r...

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