AIMC Topic: Algorithms

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Use of Deep Learning to Identify Peripheral Arterial Disease Cases From Narrative Clinical Notes.

The Journal of surgical research
INTRODUCTION: Peripheral arterial disease (PAD) is the leading cause of amputation in the United States. Despite affecting 8.5 million Americans and more than 200 million people globally, there are significant gaps in awareness by both patients and p...

Predicting Treatment Outcomes in Patients with Drug-Resistant Tuberculosis and Human Immunodeficiency Virus Coinfection, Using Supervised Machine Learning Algorithm.

Pathogens (Basel, Switzerland)
Drug-resistant tuberculosis (DR-TB) and HIV coinfection present a conundrum to public health globally and the achievement of the global END TB strategy in 2035. A descriptive, retrospective review of medical records of patients, who were diagnosed wi...

Enhancing Situational Awareness with VAS-Compass Net for the Recognition of Directional Vehicle Alert Sounds.

Sensors (Basel, Switzerland)
People with hearing impairments often face increased risks related to traffic accidents due to their reduced ability to perceive surrounding sounds. Given the cost and usage limitations of traditional hearing aids and cochlear implants, this study ai...

Tracking control problem of nonlinear strict-feedback systems with input nonlinearity: An adaptive neural network dynamic surface control method.

PloS one
In this work, the tracking control problem for a class of nonlinear strict-feedback systems with input nonlinearity is addressed. In response to the influence of input nonlinearity, an auxiliary control system is constructed to compensate for it. To ...

Deep learning innovations in South Korean maritime navigation: Enhancing vessel trajectories prediction with AIS data.

PloS one
Predicting ship trajectories can effectively forecast navigation trends and enable the orderly management of ships, which holds immense significance for maritime traffic safety. This paper introduces a novel ship trajectory prediction method utilizin...

NIDS-FGPA: A federated learning network intrusion detection algorithm based on secure aggregation of gradient similarity models.

PloS one
With the rapid development of Industrial Internet of Things (IIoT), network security issues have become increasingly severe, making intrusion detection one of the key technologies for ensuring IIoT security. However, existing intrusion detection syst...

A Multi-level ensemble approach for skin lesion classification using Customized Transfer Learning with Triple Attention.

PloS one
Skin lesions encompass a variety of skin abnormalities, including skin diseases that affect structure and function, and skin cancer, which can be fatal and arise from abnormal cell growth. Early detection of lesions and automated prediction is crucia...

Dual-hesitant fermatean fuzzy Hamacher aggregation operators and TOPSIS with their application to multi-criteria decision-making.

PloS one
The concept of the Dual-hesitant fermatean fuzzy set (DHFFS) represents a significant advancement in practical implementation, combining Fermatean fuzzy sets and Dual-hesitant sets. This new structure uses membership and non-membership hesitancy and ...

Ensemble approach for predicting the diagnosis of osteoarthritis using physical activity factors.

Journal of evaluation in clinical practice
BACKGROUND: Osteoarthritis (OA) is a common degenerative disease of the joints. Risk factors for OA include non-modifiable factors such as age and sex, as well as modifiable factors like physical activity.

Deep learning super-resolution reconstruction for fast and high-quality cine cardiovascular magnetic resonance.

European radiology
OBJECTIVES: To compare standard-resolution balanced steady-state free precession (bSSFP) cine images with cine images acquired at low resolution but reconstructed with a deep learning (DL) super-resolution algorithm.