AIMC Topic: Humans

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Novel deep reinforcement learning based collision avoidance approach for path planning of robots in unknown environment.

PloS one
Reinforcement learning is a remarkable aspect of the artificial intelligence field with many applications. Reinforcement learning facilitates learning new tasks based on action and reward principles. Motion planning addresses the navigation problem f...

A recurrence model for non-puerperal mastitis patients based on machine learning.

PloS one
OBJECTIVE: Non-puerperal mastitis (NPM) is an inflammatory breast disease affecting women during non-lactation periods, and it is prone to relapse after being cured. Accurate prediction of its recurrence is crucial for personalized adjuvant therapy, ...

Development and validation of an automated machine for self-injury assessment via young Koreans' natural writings.

PloS one
Self-injury is common in all countries, and 20% of South Korean youths experience self-injury. One of the barriers to assessment and treatment planning is the tendency of young self-injurers to conceal their identities. Following a new stream of rese...

Deep learning-based skin lesion analysis using hybrid ResUNet++ and modified AlexNet-Random Forest for enhanced segmentation and classification.

PloS one
Skin cancer is considered globally as the most fatal disease. Most likely all the patients who received wrong diagnosis and low-quality treatment die early. Though if it is detected in the early stages the patient has fairly good chance and the afore...

Machine learning and spatio-temporal analysis of meteorological factors on waterborne diseases in Bangladesh.

PLoS neglected tropical diseases
BACKGROUND: Bangladesh is facing a formidable challenge in mitigating waterborne diseases risk exacerbated by climate change. However, a comprehensive understanding of the spatio-temporal dynamics of these diseases at the district level remains elusi...

Design and realization of compressor data abnormality safety monitoring and inducement traceability expert system.

PloS one
Centrifugal compressors are widely used in the oil and natural gas industry for gas compression, reinjection, and transportation. Fault diagnosis and identification of centrifugal compressors are crucial. To promptly monitor abnormal changes in compr...

Parallel convolutional neural network and empirical mode decomposition for high accuracy in motor imagery EEG signal classification.

PloS one
In recent years, the utilization of motor imagery (MI) signals derived from electroencephalography (EEG) has shown promising applications in controlling various devices such as wheelchairs, assistive technologies, and driverless vehicles. However, de...

Multiview attention networks for fine-grained watershed categorization via knowledge distillation.

PloS one
With the rapid development of artificial intelligence technology, an increasing number of village-related modeling problems have been addressed. However, first, the exploration of village-related watershed fine-grained classification problems, partic...

A facial expression recognition network using hybrid feature extraction.

PloS one
Facial expression recognition faces great challenges due to factors such as face similarity, image quality, and age variation. Although various existing end-to-end Convolutional Neural Network (CNN) architectures have achieved good classification res...

Spatio-temporal risk prediction of leptospirosis: A machine-learning-based approach.

PLoS neglected tropical diseases
BACKGROUND: Leptospirosis is a neglected zoonotic disease prevalent worldwide, particularly in tropical regions experiencing frequent rainfall and severe cyclones, which are further aggravated by climate change. This bacterial zoonosis, caused by the...