AIMC Topic: Support Vector Machine

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Complexity Analysis based on Parietal Fuzzy Entropy to Facilitate ADHD Diagnosis in Young Children.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Attention deficit hyperactivity disorder (ADHD) is the most common condition affecting the development of neurons in children. Therefore, early and accurate diagnosis of ADHD in young children is of paramount importance. In this study, the 8-channel ...
Male Child, Preschool Humans Female Electroencephalography Signal Processing, Computer-Assisted Entropy Attention Deficit Disorder with Hyperactivity Child Support Vector Machine Fuzzy Logic
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Grade classification of nasal obstruction from endoscopy videos using machine learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Nasal obstruction (NO), referring to blockage in the nasal cavity, is prevalent, affecting approximately one-third of the adult population. Consequently, diagnosis typically requires a combination of medical imaging techniques and tests, as NO is oft...
Video Recording Nasal Obstruction Humans Machine Learning Image Processing, Computer-Assisted Support Vector Machine Endoscopy Deep Learning
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EEG Acquisition and Motor Imagery Classification for Robotic Control.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
The adoption of brain-computer interfaces (BCIs) has significantly increased in various application domains, particularly in the field of controlling robotic systems through motor imagery. The article contributes in two primary ways: 1) validating th...
Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces Movement Imagination Machine Learning Support Vector Machine Robotics Humans
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Towards Fluorescent-Tag-Less Viral Titration: Automated Estimation of Cell-Size Distribution and Infection Level from Phase-Contrast Microscopy Using Deep Learning and Transfer Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Automated detection of infected insect cells is one of the crucial tasks in the field of recombinant protein production and vaccine development. The major challenge lies in manual segmentation of cells and quantifying cell size distribution is tediou...
Automation Cell Size Microscopy, Phase-Contrast Deep Learning Image Processing, Computer-Assisted Support Vector Machine Neural Networks, Computer Animals
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Classification of Schizophrenia using Intrinsic Connectivity Networks and Incremental Boosting Convolution Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
One of the key challenges in the use of resting brain functional magnetic resonance imaging (fMRI) network analysis for predicting mental illnesses such as schizophrenia (SZ) is the high noise levels variability among individuals including age, sex, ...
Brain Female Adult Male Humans Neural Networks, Computer Algorithms Nerve Net Support Vector Machine Magnetic Resonance Imaging Schizophrenia
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Neural substrates of predicting anhedonia symptoms in major depressive disorder via connectome-based modeling.

CNS neuroscience & therapeutics Jul 1, 2024
MAIN PROBLEM: Anhedonia is a critical diagnostic symptom of major depressive disorder (MDD), being associated with poor prognosis. Understanding the neural mechanisms underlying anhedonia is of great significance for individuals with MDD, and it enco...
Magnetic Resonance Imaging Anhedonia Connectome Female Young Adult Adult Male Humans Depressive Disorder, Major Middle Aged Brain Support Vector Machine
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Classification accuracy of machine learning algorithms for Chinese local cattle breeds using genomic markers.

Yi chuan = Hereditas Jul 1, 2024
Accurate breed classification is required for the conservation and utilization of farm animal genetic resources. Traditional classification methods mainly rely on phenotypic characterization. However, it is difficult to distinguish between the highly...
Machine Learning Algorithms Animals China Support Vector Machine Cattle Genetic Markers Breeding Genomics Genome Polymorphism, Single Nucleotide
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Performance evaluation of ML models for preoperative prediction of HER2-low BC based on CE-CBBCT radiomic features: A prospective study.

Medicine Jun 14, 2024
To explore the value of machine learning (ML) models based on contrast-enhanced cone-beam breast computed tomography (CE-CBBCT) radiomics features for the preoperative prediction of human epidermal growth factor receptor 2 (HER2)-low expression breas...
Receptor, ErbB-2 Aged Adult Breast Neoplasms Cone-Beam Computed Tomography Machine Learning Radiomics Contrast Media Humans Support Vector Machine Prospective Studies Middle Aged Area Under Curve Female ROC Curve
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[Development of a grading diagnostic model for schistosomiasis-induced liver fibrosis based on radiomics and clinical laboratory indicators].

Zhongguo xue xi chong bing fang zhi za zhi = Chinese journal of schistosomiasis control Jun 7, 2024
OBJECTIVE: To investigate the feasibility of developing a grading diagnostic model for schistosomiasis-induced liver fibrosis based on B-mode ultrasonographic images and clinical laboratory indicators.
Middle Aged Liver Cirrhosis Schistosomiasis Ultrasonography Adult Humans Image Processing, Computer-Assisted Radiomics Male Machine Learning Female Support Vector Machine
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Predicting the transmission trends of COVID-19: an interpretable machine learning approach based on daily, death, and imported cases.

Mathematical biosciences and engineering : MBE Jun 3, 2024
COVID-19 is caused by the SARS-CoV-2 virus, which has produced variants and increasing concerns about a potential resurgence since the pandemic outbreak in 2019. Predicting infectious disease outbreaks is crucial for effective prevention and control....
SARS-CoV-2 Disease Outbreaks Support Vector Machine Pandemics COVID-19 Algorithms Humans Machine Learning
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