AIMC Topic: Databases, Factual

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Investigating the Role of Image Fusion in Brain Tumor Classification Models Based on Machine Learning Algorithm for Personalized Medicine.

Computational and mathematical methods in medicine
Image fusion can be performed on images either in spatial domain or frequency domain methods. Frequency domain methods will be most preferred because these methods can improve the quality of edges in an image. In image fusion, the resultant fused ima...

Multi-Task Learning With Coarse Priors for Robust Part-Aware Person Re-Identification.

IEEE transactions on pattern analysis and machine intelligence
Part-level representations are important for robust person re-identification (ReID), but in practice feature quality suffers due to the body part misalignment problem. In this paper, we present a robust, compact, and easy-to-use method called the Mul...

Study on Machine Learning Models for Building Resilience Evaluation in Mountainous Area: A Case Study of Banan District, Chongqing, China.

Sensors (Basel, Switzerland)
'Resilience' is a new concept in the research and application of urban construction. From the perspective of building adaptability in a mountainous environment and maintaining safety performance over time, this paper innovatively proposes machine lea...

Machine Learning-Based Automated Diagnostic Systems Developed for Heart Failure Prediction Using Different Types of Data Modalities: A Systematic Review and Future Directions.

Computational and mathematical methods in medicine
One of the leading causes of deaths around the globe is heart disease. Heart is an organ that is responsible for the supply of blood to each part of the body. Coronary artery disease (CAD) and chronic heart failure (CHF) often lead to heart attack. T...

Robust and generalizable embryo selection based on artificial intelligence and time-lapse image sequences.

PloS one
Assessing and selecting the most viable embryos for transfer is an essential part of in vitro fertilization (IVF). In recent years, several approaches have been made to improve and automate the procedure using artificial intelligence (AI) and deep le...

Beam Damage Assessment Using Natural Frequency Shift and Machine Learning.

Sensors (Basel, Switzerland)
Damage detection based on modal parameter changes has become popular in the last few decades. Nowadays, there are robust and reliable mathematical relations available to predict natural frequency changes if damage parameters are known. Using these re...

Interpretable Model Based on Pyramid Scene Parsing Features for Brain Tumor MRI Image Segmentation.

Computational and mathematical methods in medicine
Due to the black box model nature of convolutional neural networks, computer-aided diagnosis methods based on depth learning are usually poorly interpretable. Therefore, the diagnosis results obtained by these unexplained methods are difficult to gai...

Developing machine learning models for prediction of mortality in the medical intensive care unit.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Alert of patient deterioration is essential for prompt medical intervention in the Medical Intensive Care Unit (MICU). Logistic Regression (LR) has been used for the development of most conventional severity-of-illness scori...

Automated detection of COVID-19 through convolutional neural network using chest x-ray images.

PloS one
The COVID-19 epidemic has a catastrophic impact on global well-being and public health. More than 27 million confirmed cases have been reported worldwide until now. Due to the growing number of confirmed cases, and challenges to the variations of the...

Review on Epileptic Seizure Prediction: Machine Learning and Deep Learning Approaches.

Computational and mathematical methods in medicine
Epileptic seizures occur due to brain abnormalities that can indirectly affect patient's health. It occurs abruptly without any symptoms and thus increases the mortality rate of humans. Almost 1% of world's population suffers from epileptic seizures....