AIMC Topic: Microwaves

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Detection of carcinoembryonic antigen specificity using microwave biosensor with machine learning.

Biosensors & bioelectronics Nov 2, 2024
Early diagnosis and screening of tumor markers are essential for effective cancer treatment and improve the treatment efficiency and prognosis of tumor recurrence and metastasis. In this study, a split-ring resonator (SRR) circuit based on an interdi...
Equipment Design Biomarkers, Tumor Carcinoembryonic Antigen Biosensing Techniques Microwaves Limit of Detection Humans Machine Learning
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FT-FEDTL: A fine-tuned feature-extracted deep transfer learning model for multi-class microwave-based brain tumor classification.

Computers in biology and medicine Nov 2, 2024
The microwave brain imaging (MBI) system is an emerging technology used to detect brain tumors in their early stages. Multi-class microwave-based brain tumor (MBT) identification and classification are crucial due to the tumor's patterns and shape. M...
Image Interpretation, Computer-Assisted Microwaves Microwave Imaging Humans Brain Neoplasms Deep Learning
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A deep learning approach for non-invasive Alzheimer's monitoring using microwave radar data.

Neural networks : the official journal of the International Neural Network Society Oct 5, 2024
Over 50 million people globally suffer from Alzheimer's disease (AD), emphasizing the need for efficient, early diagnostic tools. Traditional methods like Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) scans are expensive, bulky, and s...
Humans Neuroimaging Neural Networks, Computer Deep Learning Microwaves Principal Component Analysis Brain Radar Alzheimer Disease
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Study on microwave ablation temperature prediction model based on grayscale ultrasound texture and machine learning.

PloS one Sep 25, 2024
BACKGROUND: Temperature prediction is crucial in the clinical ablation treatment of liver cancer, as it can be used to estimate the coagulation zone of microwave ablation.
Ultrasonography Temperature Liver Neoplasms Machine Learning Animals Liver Microwaves Swine Algorithms Ablation Techniques
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Machine Learning Based on Clinical Information and Integrated CT Radiomics to Predict Local Recurrence of Stage Ia Lung Adenocarcinoma after Microwave Ablation.

Journal of vascular and interventional radiology : JVIR Aug 28, 2024
PURPOSE: To develop and compare 3 different machine learning-based models of clinical information and integrated radiomics features predicting the local recurrence of Stage Ia lung adenocarcinoma after microwave ablation (MWA) for assisting clinical ...
Machine Learning Decision Support Techniques Retrospective Studies Margins of Excision Tomography, X-Ray Computed Adenocarcinoma of Lung Clinical Decision-Making Ablation Techniques Female Neoplasm Recurrence, Local Microwaves Humans Time Factors Male Predictive Value of Tests Risk Factors Lung Neoplasms Middle Aged Aged Neoplasm Staging Treatment Outcome Risk Assessment Radiomics Radiographic Image Interpretation, Computer-Assisted
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A surrogate-assisted extended generative adversarial network for parameter optimization in free-form metasurface design.

Neural networks : the official journal of the International Neural Network Society Aug 22, 2024
Metasurfaces have widespread applications in fifth-generation (5G) microwave communication. Among the metasurface family, free-form metasurfaces excel in achieving intricate spectral responses compared to regular-shape counterparts. However, conventi...
Neural Networks, Computer Algorithms Deep Learning Microwaves
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Feasibility of Artificial Intelligence Powered Adverse Event Analysis: Using a Large Language Model to Analyze Microwave Ablation Malfunction Data.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes Aug 21, 2024
Determine if a large language model (LLM, GPT-4) can label and consolidate and analyze interventional radiology (IR) microwave ablation device safety event data into meaningful summaries similar to humans. Microwave ablation safety data from Januar...
Ablation Techniques Equipment Failure Feasibility Studies Microwaves Humans Artificial Intelligence
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Microwave detection technique combined with deep learning algorithm facilitates quantitative analysis of heavy metal Pb residues in edible oils.

Journal of food science Aug 13, 2024
The heavy metal content in edible oils is intricately associated with their suitability for human consumption. In this study, standard soybean oil was used as a sample to quantify the specified concentration of heavy metals using microwave sensing te...
Neural Networks, Computer Algorithms Plant Oils Microwaves Metals, Heavy Deep Learning Food Contamination Lead Soybean Oil
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Ultrasound Image Temperature Monitoring Based on a Temporal-Informed Neural Network.

Sensors (Basel, Switzerland) Jul 30, 2024
Real-time and accurate temperature monitoring during microwave hyperthermia (MH) remains a critical challenge for ensuring treatment efficacy and patient safety. This study presents a novel approach to simulate real MH and precisely determine the tem...
Phantoms, Imaging Hyperthermia, Induced Ultrasonography Microwaves Temperature Animals Swine Humans Neural Networks, Computer
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Near-field microwave sensing technology enhanced with machine learning for the non-destructive evaluation of packaged food and beverage products.

Scientific reports Jun 11, 2024
In the food industry, the increasing use of automatic processes in the production line is contributing to the higher probability of finding contaminants inside food packages. Detecting these contaminants before sending the products to market has beco...
Food Contamination Food Analysis Beverages Algorithms Microwaves Machine Learning Support Vector Machine Food Packaging
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