AIMC Topic: Algorithms

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A multi-layered defense against adversarial attacks in brain tumor classification using ensemble adversarial training and feature squeezing.

Scientific reports
Deep learning, particularly convolutional neural networks (CNNs), has proven valuable for brain tumor classification, aiding diagnostic and therapeutic decisions in medical imaging. Despite their accuracy, these models are vulnerable to adversarial a...

Predictors and associations of complications in ureteroscopy for stone disease using AI: outcomes from the FLEXOR registry.

Urolithiasis
We aimed to develop machine learning(ML) algorithms to evaluate complications of flexible ureteroscopy and laser lithotripsy(fURSL), providing a valid predictive model. 15 ML algorithms were trained on a large number fURSL data from > 6500 patients f...

Utilizing Image Processing Techniques for Wound Management and Evaluation in Clinical Practice: Establishing the Feasibility of Implementing Artificial Intelligence in Routine Wound Care.

Advances in skin & wound care
OBJECTIVE: To develop a generalizable and accurate method for automatically analyzing wound images captured in clinical practice and extracting key wound characteristics such as surface area measurement.

Ethics: Crisis Standards of Care Simulation.

Advanced emergency nursing journal
Ethical dilemmas exist with decision-making regarding resource allocations, such as critical care, ventilators and other critical equipment, and pharmaceuticals during pandemics. Triage artificial intelligence (AI) algorithms based on prognostication...

A Software-Defined Sensor System Using Semantic Segmentation for Monitoring Remaining Intravenous Fluids.

Sensors (Basel, Switzerland)
Accurate intravenous (IV) fluid monitoring is critical in healthcare to prevent infusion errors and ensure patient safety. Traditional monitoring methods often depend on dedicated hardware, such as weight sensors or optical systems, which can be cost...

Prediction models based on machine learning algorithms for COVID-19 severity risk.

BMC public health
BACKGROUND: The World Health Organization has highlighted the risk of Disease X, urging pandemic preparedness. Coronavirus disease 2019 (COVID-19) could be the first Disease X; therefore, understanding the epidemiological experiences of COVID-19 is c...

A novel hybrid fruit fly and simulated annealing optimized faster R-CNN for detection and classification of tomato plant leaf diseases.

Scientific reports
Modern agriculture increasingly relies on technologies that enhance farmers' efficiency and economic growth. One challenge is the accurate identification of disease-affected plants, whose characteristics like structure, size, texture, and color can v...

Detection of sugar beet seed coating defects via deep learning.

Scientific reports
The global seed coating market is expected to experience substantial growth, increasing from a 2023 valuation of USD 2.0 billion to an estimated value of USD 3.1 billion by 2028. This growth surge is primarily due to the consistent introduction of in...

Revolutionizing sleep disorder diagnosis: A Multi-Task learning approach optimized with genetic and Q-Learning techniques.

Scientific reports
Adequate sleep is crucial for maintaining a healthy lifestyle, and its deficiency can lead to various sleep-related disorders. Identifying these disorders early is essential for effective treatment, which traditionally relies on polysomnogram (PSG) t...

Optimized SVR with nature-inspired algorithms for environmental modelling of mycotoxins in food virtual-water samples.

Scientific reports
The accurate determination of mycotoxins in food samples is crucial to guarantee food safety and minimize their toxic effects on human and animal health. This study proposed the use of a support vector regression (SVR) predictive model improved by tw...