Devices and Vaccines

Comparison of Artificial Intelligence Tools With Human Coding for Sentiment, Topic, and Thematic Analysis Tasks of Public Health Datasets During the COVID-19 Pandemic in Australia: Case Study.

BACKGROUND: Public opinion, which may be influenced by personal experiences, news, and social media, can impact compliance with public health measures (PHMs) during health emergencies. Artificial intelligence (AI) tools offer opportunities to analyze public opinion in real time during health emergencies. However, their performance in accurately identifying sentiment and themes in health-related on...

Adults' dental cone beam computed tomography images dataset for detecting and classifying missing teeth.

The scarcity of high-quality Cone Beam Computed Tomography (CBCT) datasets with Three-Dimensional (3D) annotations hinders advancements in automated dental implant planning. Existing datasets lack precise 3D localization of tooth loss sites, particularly in complex cases presenting metal artifacts or existing implants. To address this, we curated a CBCT dataset from 158 patients across three insti...

AI-Enhanced Automatic Life Story Structuring for Reminiscence Therapy in Older Adults: Technical Feasibility Study.

BACKGROUND: Storytelling interventions have demonstrated substantial potential in improving emotional well-being, cognitive function, and quality of l...

A Cantilever-Based Broadband Acoustoelectric Device with Aligned PVDF-HFP Nanofibers for Self-Powered Sensing and High-Accuracy Speech Recognition.

As the adoption of acoustic sensing grows in speech recognition, health monitoring, and the Internet of Things, the limited broadband response of flex...

Development and Validation of a Machine Learning-Based Model to Predict Peri-Implant Mucositis in Patients With Dental Implant Placement After 1-Year.

OBJECTIVES: To develop and validate an interpretable machine learning (ML) model for early prediction of peri-implant mucositis (PIM). MATERIAL AND ME...

High-Throughput Image-Based Pupal Sex Classification in Aedes aegypti Using Convolutional Neural Network Models for Sterile Insect Technique Applications.

Aedes aegypti, the primary vector of dengue, yellow fever, Zika, and chikungunya, poses serious public health threats, especially in tropical regions....

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures.

Unprecedented advances in Artificial Intelligence (AI)-assisted automation continue to drive the demand for hardware that is significantly more scalab...

"Can a chatbot be used in the full-text screening in a systematic review?".

INTRODUCTION: Large language model-based artificial intelligence tools are increasingly explored to support systematic reviews, yet evidence regarding...

Efficacy of swine Influenza A virus vaccines on transmission, viral shedding and clinical signs: Systematic review and meta-analysis.

Swine influenza A viruses (swIAV) are a major cause of respiratory disease in pigs, and vaccination remains the main control strategy. The objective o...

Deterioration of immunization resilience: A Bayesian machine learning assessment of the 2025-2026 measles outbreak in Mexico.

OBJECTIVE: The 2025 measles outbreak in Mexico (5741 cases) marked a severe decline in immunization resilience. We aimed to measure this systemic vuln...

mRNA vaccines in cancer immunotherapy: current progress and perspectives in solid tumors and hematologic malignancies.

The unprecedented success of mRNA vaccines during the COVID-19 pandemic has accelerated the development of nucleic acid-based therapeutics, particular...

Geometric-Driven Cross-Modal Registration Framework for Optical Scanning and CBCT Models in AR-Based Maxillofacial Surgical Navigation.

OBJECTIVE: Accurate preoperative planning for dental implants, especially in edentulous or partially edentulous patients, relies on precise localizati...

Leveraging Self-Supervised Audio-Visual Pretrained Models to Improve Vocoded Speech Intelligibility in Cochlear Implant Simulation.

OBJECTIVE: Individuals with hearing impairments face challenges in their ability to comprehend speech, particularly in noisy environments. This study ...

Detection and Classification of Peri-Implant Marginal Bone Loss in Cone-Beam Computed Tomography Using a Deep Learning Approach.

OBJECTIVES: Modern dental implants have high long-term survival, but peri-implant marginal bone loss remains a multifactorial cause of implant failure...

Early Prediction of Hepatic Decompensation in Cirrhosis Using Optimised XGBoost Models at the Initial Outpatient Hepatology Visit.

BACKGROUND AND AIMS: Hepatic decompensation represents a critical transition in cirrhosis, leading to increased morbidity, mortality and healthcare ut...

Deep Learning-Enhanced Resonance Frequency Analysis for Dental Implant Stability Assessment.

OBJECTIVES: Accurate assessment of dental implant stability is critical for predicting osseointegration outcomes and guiding clinical decision-making....

Single-molecule neuromorphic device with aJ-level power consumption per switching.

Artificial neural network-based machine learning provides foundations for artificial intelligence (AI), yet requires high energy costs for training. B...

A hybrid spiking convolutional neural framework with extreme learning machine for enhanced anomaly detection in network security.

Real-time cybersecurity systems continue to have a significant problem in detecting breaches in dynamic and highly unbalanced network streams. An onli...

Assessing the Predictive Value of Kolmogorov-Arnold Networks for the No-Reflow Phenomenon in ST-Segment Elevation Myocardial Infarction: A Comparative Machine Learning Study.

OBJECTIVE: The no-reflow phenomenon in ST-segment elevation myocardial infarction (STEMI) is a significant clinical issue associated with poor cardiov...

Dynamic-Aware video distillation: Adaptive temporal partitioning based on video semantics for edge device.

Deep learning model training on edge device is challenged by limited computational power and dataset scale. Dataset distillation (DD) aims to address ...