AIMC Topic: Algorithms

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Risk assessment of corn borer based on feature optimization and weighted spatial clustering: a case study in Shandong Province, China.

Scientific reports
As a typical pest affecting corn yield and safety, corn borer causes serious economic losses worldwide. Climate warming has intensified the occurrence of pest outbreaks in recent years, but the associated risk has not been precisely assessed or under...

Investigating the Impact of the Stationarity Hypothesis on Heart Failure Detection using Deep Convolutional Scattering Networks and Machine Learning.

Scientific reports
Detection of Cardiovascular Diseases (CVDs) has become crucial nowadays, as the World Health Organization (WHO) declares CVDs as the major leading causes of death in the globe. Moreover, the death rate due to CVDs is expected to rise in the next few ...

Parkinson disease detection based on in-air dynamics feature extraction and selection using machine learning.

Scientific reports
Parkinson's disease (PD) is a progressive neurological disorder that impairs movement control, leading to symptoms such as tremors, stiffness, and bradykinesia. Early and accurate PD detection is essential for effective management and improving patie...

Data Collection for Automatic Depression Identification in Spanish Speakers Using Deep Learning Algorithms: Protocol for a Case-Control Study.

JMIR research protocols
BACKGROUND: Depression is a mental health condition that affects millions of people worldwide. Although common, it remains difficult to diagnose due to its heterogeneous symptomatology. Mental health questionnaires are currently the most used assessm...

Automating Colon Polyp Classification in Digital Pathology by Evaluation of a "Machine Learning as a Service" AI Model: Algorithm Development and Validation Study.

JMIR formative research
BACKGROUND: Artificial intelligence (AI) models are increasingly being developed to improve the efficiency of pathological diagnoses. Rapid technological advancements are leading to more widespread availability of AI models that can be used by domain...

Explainable machine learning for predicting ICU mortality in myocardial infarction patients using pseudo-dynamic data.

Scientific reports
Myocardial infarction (MI) remains one of the greatest contributors to mortality, and patients admitted to the intensive care unit (ICU) with myocardial infarction are at higher risk of death. In this study, we use two retrospective cohorts extracted...

AI-Driven fetal distress monitoring SDN-IoMT networks.

PloS one
The healthcare industry is transforming with the integration of the Internet of Medical Things (IoMT) with AI-powered networks for improved clinical connectivity and advanced monitoring capabilities. However, IoMT devices struggle with traditional ne...

A bearing fault diagnosis method based on hybrid artificial intelligence models.

PloS one
The working state of rolling bearing severely affects the performance of industrial equipment. Addressing the issue of that the difficulty of incipient weak signals feature extraction influences the rolling bearing diagnosis accuracy, an efficient be...

PairReg: A method for enhancing the learning of molecular structure representation in equivariant graph neural networks.

PloS one
The 3D structure of molecules contains a wealth of important information, but traditional 3DCNN-based methods fail to adequately address the transformations of rigid motions (rotation, translation, and mapping). Equivariant graph neural networks (EGN...

A long-term localization and mapping system for autonomous inspection robots in large-scale environments using 3D LiDAR sensors.

PloS one
Inspection mobile robots equipped with 3D LiDAR sensors are now widely used in substations and other critical circumstances. However, the application of traditional LiDAR sensors is restricted in large-scale environments. Prolonged operation poses th...