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Understanding the Perceptions of Healthcare Researchers Regarding ChatGPT: A Study Based on Bidirectional Encoder Representation from Transformers (BERT) Sentiment Analysis and Topic Modeling.

Annals of biomedical engineering
In this study, we have used deep learning techniques to understand the perception of researchers in the healthcare sector about the recently introduced chat generative pre-trained transformer (ChatGPT). Ever since the launch of ChatGPT, there have be...

Potential Use of Artificial Intelligence in Infectious Disease: Take ChatGPT as an Example.

Annals of biomedical engineering
Over the past month, a new AI model called Chatbot Generative Pre-trained Transformer (ChatGPT), has received enormous attention in the media and scientific communities due to its ability to process and respond to commands in a humanistic fashion. As...

Talk with ChatGPT About the Outbreak of Mpox in 2022: Reflections and Suggestions from AI Dimensions.

Annals of biomedical engineering
In the era of big data, generative artificial intelligence (AI) models are currently in a boom. The Chatbot Generative Pre-trained Transformer (ChatGPT), a large language model (LLM) developed by OpenAI (San Francisco, CA), is a type of AI software t...

G2GT: Retrosynthesis Prediction with Graph-to-Graph Attention Neural Network and Self-Training.

Journal of chemical information and modeling
Retrosynthesis prediction, the task of identifying reactant molecules that can be used to synthesize product molecules, is a fundamental challenge in organic chemistry and related fields. To address this challenge, we propose a novel graph-to-graph t...

Yolo-Pest: An Insect Pest Object Detection Algorithm via CAC3 Module.

Sensors (Basel, Switzerland)
Insect pests have always been one of the main hazards affecting crop yield and quality in traditional agriculture. An accurate and timely pest detection algorithm is essential for effective pest control; however, the existing approach suffers from a ...

Object Detection Based on Swin Deformable Transformer-BiPAFPN-YOLOX.

Computational intelligence and neuroscience
Object detection technology plays a crucial role in people's everyday lives, as well as enterprise production and modern national defense. Most current object detection networks, such as YOLOX, employ convolutional neural networks instead of a Transf...

EG-TransUNet: a transformer-based U-Net with enhanced and guided models for biomedical image segmentation.

BMC bioinformatics
Although various methods based on convolutional neural networks have improved the performance of biomedical image segmentation to meet the precision requirements of medical imaging segmentation task, medical image segmentation methods based on deep l...

Pathway of transient electronics towards connected biomedical applications.

Nanoscale
Transient electronic devices have shown promising applications in hardware security and medical implants with diagnosing therapeutics capabilities since their inception. Control of the device transience allows the device to "dissolve at will" after i...

HMFT: Hyperspectral and Multispectral Image Fusion Super-Resolution Method Based on Efficient Transformer and Spatial-Spectral Attention Mechanism.

Computational intelligence and neuroscience
Due to the imaging mechanism of hyperspectral images, the spatial resolution of the resulting images is low. An effective method to solve this problem is to fuse the low-resolution hyperspectral image (LR-HSI) with the high-resolution multispectral i...

Development and Validation of Deep Learning Models for the Multiclassification of Reflux Esophagitis Based on the Los Angeles Classification.

Journal of healthcare engineering
This study is to evaluate the feasibility of deep learning (DL) models in the multiclassification of reflux esophagitis (RE) endoscopic images, according to the Los Angeles (LA) classification for the first time. The images were divided into three gr...