AIMC Topic: Algorithms

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An Ensemble Learning Algorithm for Cognitive Evaluation by an Immersive Virtual Reality Supermarket.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Early screening for Mild Cognitive Impairment (MCI) is crucial in delaying cognitive deterioration and treating dementia. Conventional neuropsychological tests, commonly used for MCI detection, often lack ecological validity due to their simplistic a...

Determining domestic violence against women using machine learning methods: The case of Türkiye.

Journal of evaluation in clinical practice
BACKGROUND: Domestic violence against women is a pervasive issue globally, representing a severe violation of human rights and a significant public health concern. The hidden nature of such violence and its frequent underreporting make it a critical ...

Leveraging explainable machine learning for enhanced management of lake water quality.

Journal of environmental management
Freshwater lakes worldwide suffer from eutrophication caused by excessive nutrient loads, particularly nitrogen (N) and phosphorus (P) from wastewater and runoff, affecting aquatic life and public health. Using a large (1800 km) subtropical lake as a...

GraphPI: Efficient Protein Inference with Graph Neural Networks.

Journal of proteome research
The integration of deep learning approaches in biomedical research has been transformative, enabling breakthroughs in various applications. Despite these strides, its application in protein inference is impeded by the scarcity of extensively labeled ...

Graph based recurrent network for context specific synthetic lethality prediction.

Science China. Life sciences
The concept of synthetic lethality (SL) has been successfully used for targeted therapies. To further explore SL for cancer therapy, identifying more SL interactions with therapeutic potential are essential. Recently, graph neural network-based deep ...

A machine learning algorithm for creating isotropic 3D aortic segmentations from routine cardiac MR localizers.

Magnetic resonance imaging
BACKGROUND: The identification and measurement of aortic aneurysms is an important clinical problem. While specialized high-resolution 3D CMR sequences allow detailed aortic assessment, they are time-consuming which limits their use in screening rout...

Integrating color histogram analysis and convolutional neural networks for skin lesion classification.

Computers in biology and medicine
The color of skin lesions is a crucial diagnostic feature for identifying malignant melanoma and other skin diseases. Typical colors associated with melanocytic lesions include tan, brown, black, red, white, and blue-gray. This study introduces a nov...

Considerations for using tree-based machine learning to assess causation between demographic and environmental risk factors and health outcomes.

Environmental science and pollution research international
Evaluation of the heterogeneous treatment effect (HTE) allows for the assessment of the causal effect of a therapy or intervention while considering heterogeneity in individual factors within a population. Machine learning (ML) methods have previousl...

Haves and have-nots: socioeconomic position improves accuracy of machine learning algorithms for predicting high-impact chronic pain.

Pain
Lower socioeconomic position (SEP) is associated with increased risk of developing chronic pain, experiencing more severe pain, and suffering greater pain-related disability. However, SEP is a multidimensional construct; there is a dearth of research...

Open-set long-tailed recognition via orthogonal prototype learning and false rejection correction.

Neural networks : the official journal of the International Neural Network Society
Learning from data with long-tailed and open-ended distributions is highly challenging. In this work, we propose OLPR, which is a new dual-stream Open-set Long-tailed recognition framework based on orthogonal Prototype learning and false Rejection co...