AIMC Topic: Algorithms

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Machine learning to predict occult nodal metastasis in early oral squamous cell carcinoma.

Oral oncology
OBJECTIVES: To develop and validate an algorithm to predict occult nodal metastasis in clinically node negative oral cavity squamous cell carcinoma (OCSCC) using machine learning. To compare algorithm performance to a model based on tumor depth of in...

Exponential H∞ Filtering for Continuous-Time Switched Neural Networks Under Persistent Dwell-Time Switching Regularity.

IEEE transactions on cybernetics
This paper focuses on the exponential H filtering issue for a class of continuous-time switched neural networks (NNs). Our aim is to design a mode-dependent filter acquiring the state of the investigated system, and ensuring the global uniform expone...

Automatic Sleep Staging Employing Convolutional Neural Networks and Cortical Connectivity Images.

IEEE transactions on neural networks and learning systems
Understanding of the neuroscientific sleep mechanisms is associated with mental/cognitive and physical well-being and pathological conditions. A prerequisite for further analysis is the identification of the sleep macroarchitecture through manual sle...

Multi-parametric MRI-based radiomics signature for discriminating between clinically significant and insignificant prostate cancer: Cross-validation of a machine learning method.

European journal of radiology
PURPOSE: To evaluate the performance of a multi-parametric MRI (mp-MRI)-based radiomics signature for discriminating between clinically significant prostate cancer (csPCa) and insignificant PCa (ciPCa).

Adaptive Fruitfly Based Modified Region Growing Algorithm for Cardiac Fat Segmentation Using Optimal Neural Network.

Journal of medical systems
Epicardial adipose tissue is a visceral fat that has remained an entity of concern for decades owing to its high correlation with coronary heart disease. It continues to stump medical practitioners on the pretext of its relevance with pericardial fat...

Objective Relationship Between Sleep Apnea and Frequency of Snoring Assessed by Machine Learning.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
STUDY OBJECTIVES: Snoring is perceived to be directly proportional to sleep apnea severity, especially obstructive sleep apnea (OSA), but this notion has not been thoroughly and objectively evaluated, despite its popularity in clinical practice. This...

A Comparison of Some Nature-Inspired Optimization Metaheuristics Applied in Biomedical Image Registration.

Methods of information in medicine
UNLABELLED: Computational Intelligence Re-meets Medical Image Processing Analysis of Machine Learning Algorithms for Diagnosis of Diffuse Lung Diseases BACKGROUND:  In the last decades, new optimization methods based on the nature's intelligence were...

Analysis of Machine Learning Algorithms for Diagnosis of Diffuse Lung Diseases.

Methods of information in medicine
UNLABELLED: Computational Intelligence Re-meets Medical Image Processing A Comparison of Some Nature-Inspired Optimization Metaheuristics Applied in Biomedical Image Registration BACKGROUND:  Diffuse lung diseases (DLDs) are a diverse group of pulmon...