AIMC Topic: Support Vector Machine

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Prediction of landfill gases concentration based on Grey Wolf Optimization - Support Vector Regression during landfill excavation process.

Waste management (New York, N.Y.) Mar 4, 2025
In some areas, there is a phenomenon that the landfill is full or even over-capacity with the extension of the service period. With the aging and damage of the protective facilities, this phenomenon may have a more serious impact on the surrounding e...
Environmental Monitoring Algorithms Refuse Disposal Support Vector Machine Waste Disposal Facilities Air Pollutants Odorants Gases
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Novelty Recognition: Fish Species Classification via Open-Set Recognition.

Sensors (Basel, Switzerland) Mar 4, 2025
To support the sustainable use of marine resources, regulations have been proposed to reduce fish discards focusing on the registration of all listed species. To comply with such regulations, computer vision methods have been developed. Nevertheless,...
Fishes Pattern Recognition, Automated Algorithms Animals Support Vector Machine
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Breast cancer prediction based on gene expression data using interpretable machine learning techniques.

Scientific reports Mar 4, 2025
Breast cancer remains a global health burden, with an increase in deaths related to this particular cancer. Accurately predicting and diagnosing breast cancer is important for treatment development and survival of patients. This study aimed to accura...
Female Breast Neoplasms Gene Expression Profiling Support Vector Machine Computational Biology Gene Expression Regulation, Neoplastic Humans Machine Learning
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Machine learning-based classification of spatially resolved diffuse reflectance and autofluorescence spectra acquired on human skin for actinic keratoses and skin carcinoma diagnostics aid.

Journal of biomedical optics Mar 4, 2025
SIGNIFICANCE: The incidence of keratinocyte carcinomas (KCs) is increasing every year, making the task of developing new methods for KC early diagnosis of utmost medical and economical importance.
Keratosis, Actinic Skin Neoplasms Discriminant Analysis Carcinoma, Basal Cell Skin Carcinoma, Squamous Cell Humans Aged Optical Imaging Middle Aged Support Vector Machine Machine Learning Aged, 80 and over Diagnosis, Computer-Assisted Spectrometry, Fluorescence Female Male
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Predictive modeling and optimization in dermatology: Machine learning for skin disease classification.

Computers in biology and medicine Mar 3, 2025
The accurate diagnosis of skin diseases is crucial for effective patient management and treatment, yet traditional diagnostic methods often involve subjective interpretation and can lead to variability in outcomes. In this study, we harness the power...
Humans Skin Diseases Machine Learning Dermatology Diagnosis, Computer-Assisted Support Vector Machine
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Deep Learning-Based Diagnostic Model for Parkinson's Disease Using Handwritten Spiral and Wave Images.

Current medical science Mar 3, 2025
OBJECTIVE: To develop and validate a deep neural network (DNN) model for diagnosing Parkinson's Disease (PD) using handwritten spiral and wave images, and to compare its performance with various machine learning (ML) and deep learning (DL) models.
Female Sensitivity and Specificity Male Deep Learning Humans Neural Networks, Computer Handwriting Image Processing, Computer-Assisted Support Vector Machine Parkinson Disease
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MRI radiomics based on machine learning in high-grade gliomas as a promising tool for prediction of CD44 expression and overall survival.

Scientific reports Mar 3, 2025
We aimed to predict CD44 expression and assess its prognostic significance in patients with high-grade gliomas (HGG) using non-invasive radiomics models based on machine learning. Enhanced magnetic resonance imaging, along with the corresponding gene...
Support Vector Machine Magnetic Resonance Imaging Neoplasm Grading Kaplan-Meier Estimate Middle Aged ROC Curve Glioma Hyaluronan Receptors Female Aged Adult Brain Neoplasms Male Radiomics Biomarkers, Tumor Humans Machine Learning Prognosis
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Diffusion-Weighted Imaging-Based Radiomics Features and Machine Learning Method to Predict the 90-Day Prognosis in Patients With Acute Ischemic Stroke.

The neurologist Mar 1, 2025
OBJECTIVES: The evaluation of the prognosis of patients with acute ischemic stroke (AIS) is of great significance in clinical practice. We aim to evaluate the feasibility and effectiveness of diffusion-weighted imaging (DWI) image-based radiomics fea...
Support Vector Machine Prognosis Ischemic Stroke Female Diffusion Magnetic Resonance Imaging Male Humans Aged, 80 and over Aged Middle Aged Machine Learning Radiomics
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Predicting responsiveness to fixed-dose methylene blue in adult patients with septic shock using interpretable machine learning: a retrospective study.

Scientific reports Mar 1, 2025
This study aimed to develop an interpretable machine learning model to predict methylene blue (MB) responsiveness in adult patients with refractory septic shock and to identify key factors influencing MB responsiveness using the SHapley Additive exPl...
Treatment Outcome Support Vector Machine Methylene Blue Humans Machine Learning Middle Aged Retrospective Studies Shock, Septic Female Adult Aged Male
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Development and multi-center cross-setting validation of an explainable prediction model for sarcopenic obesity: a machine learning approach based on readily available clinical features.

Aging clinical and experimental research Mar 1, 2025
OBJECTIVES: Sarcopenic obesity (SO), characterized by the coexistence of obesity and sarcopenia, is an increasingly prevalent condition in aging populations, associated with numerous adverse health outcomes. We aimed to identify and validate an expla...
Humans Machine Learning Female Aged ROC Curve Support Vector Machine Obesity Sarcopenia Aged, 80 and over Male China
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