AIMC Topic: Electric Power Supplies

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MAEF-Net: MLP Attention for Feature Enhancement in U-Net based Medical Image Segmentation Networks.

IEEE journal of biomedical and health informatics
Medical image segmentation plays an important role in diagnosis. Since the introduction of U-Net, numerous advancements have been implemented to enhance its performance and expand its applicability. The advent of Transformers in computer vision has l...

CellT-Net: A Composite Transformer Method for 2-D Cell Instance Segmentation.

IEEE journal of biomedical and health informatics
Cell instance segmentation (CIS) via light microscopy and artificial intelligence (AI) is essential to cell and gene therapy-based health care management, which offers the hope of revolutionary health care. An effective CIS method can help clinicians...

Artificial intelligence model GPT4 narrowly fails simulated radiological protection exam.

Journal of radiological protection : official journal of the Society for Radiological Protection
This study assesses the efficacy of Generative Pre-Trained Transformers (GPT) published by OpenAI in the specialised domains of radiological protection and health physics. Utilising a set of 1064 surrogate questions designed to mimic a health physics...

Differentiating ChatGPT-Generated and Human-Written Medical Texts: Quantitative Study.

JMIR medical education
BACKGROUND: Large language models, such as ChatGPT, are capable of generating grammatically perfect and human-like text content, and a large number of ChatGPT-generated texts have appeared on the internet. However, medical texts, such as clinical not...

GPDRP: a multimodal framework for drug response prediction with graph transformer.

BMC bioinformatics
BACKGROUND: In the field of computational personalized medicine, drug response prediction (DRP) is a critical issue. However, existing studies often characterize drugs as strings, a representation that does not align with the natural description of m...

A knowledge-guided pre-training framework for improving molecular representation learning.

Nature communications
Learning effective molecular feature representation to facilitate molecular property prediction is of great significance for drug discovery. Recently, there has been a surge of interest in pre-training graph neural networks (GNNs) via self-supervised...

Transformer based neural network for daily ground settlement prediction of foundation pit considering spatial correlation.

PloS one
Deep foundation pit settlement prediction based on machine learning is widely used for ensuring the safety of construction, but previous studies are limited to not fully considering the spatial correlation between monitoring points. This paper propos...

MetaQA: Enhancing human-centered data search using Generative Pre-trained Transformer (GPT) language model and artificial intelligence.

PloS one
Accessing and utilizing geospatial data from various sources is essential for developing scientific research to address complex scientific and societal challenges that require interdisciplinary knowledge. The traditional keyword-based geosearch appro...

Performance analysis of PID controller and fuzzy logic controller for DC-DC boost converter.

PloS one
Demand of Power electronics converter is increased due to the rapid increase of green re-sources. The distributed nature of uncontrolled renewable energy resources are connected with the grid via power electronics converter. DC-DC converters are high...

Multispectral Plant Disease Detection with Vision Transformer-Convolutional Neural Network Hybrid Approaches.

Sensors (Basel, Switzerland)
Plant diseases pose a critical threat to global agricultural productivity, demanding timely detection for effective crop yield management. Traditional methods for disease identification are laborious and require specialised expertise. Leveraging cutt...