AIMC Topic: Algorithms

Clear Filters Showing 3701 to 3710 of 28713 articles

A meta-learning imbalanced classification framework via boundary enhancement strategy with Bayes imbalance impact index.

Neural networks : the official journal of the International Neural Network Society
For imbalanced classification problem, algorithm-level methods can effectively avoid the information loss and noise introduction of data-level methods. However, the differences in the characteristics of the datasets, such as imbalance ratio, data dim...

Fuzzy bifocal disambiguation for partial multi-label learning.

Neural networks : the official journal of the International Neural Network Society
In partial multi-label learning (PML), each instance is associated with multiple candidate labels, but only a subset is the ground-truth label. Due to the ambiguous label information, PML is more challenging than traditional multi-label learning. Con...

Dynamic spectrum-driven hierarchical learning network for polyp segmentation.

Medical image analysis
Accurate automatic polyp segmentation in colonoscopy is crucial for the prompt prevention of colorectal cancer. However, the heterogeneous nature of polyps and differences in lighting and visibility conditions present significant challenges in achiev...

Swarm-initialized adaptive controller with beetle antenna searching of wearable lower limb exoskeleton for sit-to-stand and walking motions.

ISA transactions
In recent years, exoskeleton robots have attracted great interest from researchers in the area of robotics due to their ability to assist human functionality improvement. A wearable lower limb exoskeleton is aimed at supporting the limb functionality...

Sleep Posture Detection via Embedded Machine Learning on a Reduced Set of Pressure Sensors.

Sensors (Basel, Switzerland)
Sleep posture is a key factor in assessing sleep quality, especially for individuals with Obstructive Sleep Apnea (OSA), where the sleeping position directly affects breathing patterns: the side position alleviates symptoms, while the supine position...

Development of Predictive Model of Surgical Case Durations Using Machine Learning Approach.

Journal of medical systems
Optimizing operating room (OR) utilization is critical for enhancing hospital management and operational efficiency. Accurate surgical case duration predictions are essential for achieving this optimization. Our study aimed to refine the accuracy of ...

Machine learning prediction model for oral mucositis risk in head and neck radiotherapy: a preliminary study.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
PURPOSE: Oral mucositis (OM) reflects a complex interplay of several risk factors. Machine learning (ML) is a promising frontier in science, capable of processing dense information. This study aims to assess the performance of ML in predicting OM ris...

Development and evaluation of interpretable machine learning regressors for predicting femoral neck bone mineral density in elderly men using NHANES data.

Biomolecules & biomedicine
Osteoporotic femoral neck fractures (OFNFs) pose a significant orthopedic challenge in the elderly population, accounting for up to 40% of all osteoporotic fractures and leading to considerable health deterioration and increased mortality. In address...

Illustration image style transfer method design based on improved cyclic consistent adversarial network.

PloS one
To improve the expressiveness and realism of illustration images, the experiment innovatively combines the attention mechanism with the cycle consistency adversarial network and proposes an efficient style transfer method for illustration images. The...

Enhancing stock index prediction: A hybrid LSTM-PSO model for improved forecasting accuracy.

PloS one
Stock price prediction is a challenging research domain. The long short-term memory neural network (LSTM) widely employed in stock price prediction due to its ability to address long-term dependence and transmission of historical time signals in time...