Support Vector Machine

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...

Humans Machine Learning Female Gene Expression Regulation, Neoplastic Support Vector Machine Breast Neoplasms Gene Expression Profiling Computational Biology

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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.

Discriminant Analysis Female Skin Skin Neoplasms Optical Imaging Carcinoma, Basal Cell Keratosis, Actinic Carcinoma, Squamous Cell Middle Aged Aged Humans Diagnosis, Computer-Assisted Aged, 80 and over Machine Learning Support Vector Machine Male Spectrometry, Fluorescence

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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...

Diagnosis, Computer-Assisted Humans Support Vector Machine Machine Learning Skin Diseases Dermatology

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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.

Humans Neural Networks, Computer Female Sensitivity and Specificity Image Processing, Computer-Assisted Male Support Vector Machine Deep Learning Parkinson Disease Handwriting

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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...

Male Middle Aged ROC Curve Glioma Radiomics Biomarkers, Tumor Brain Neoplasms Hyaluronan Receptors Support Vector Machine Magnetic Resonance Imaging Neoplasm Grading Kaplan-Meier Estimate Humans Machine Learning Prognosis Female Aged Adult

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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...

Diffusion Magnetic Resonance Imaging Male Middle Aged Support Vector Machine Ischemic Stroke Humans Aged Machine Learning Aged, 80 and over Prognosis Radiomics Female

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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...

Methylene Blue Shock, Septic Treatment Outcome Support Vector Machine Humans Machine Learning Retrospective Studies Female Aged Adult Male Middle Aged

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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 ROC Curve Support Vector Machine Obesity Sarcopenia Aged Aged, 80 and over Male China

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Sliding-window enhanced olfactory visual images combined with deep learning to predict TVB-N content in chilled mutton.

Meat science Feb 28, 2025

A novel data enhancement method for olfactory visual images was proposed in this study, combined with deep learning to achieve the accurate prediction of total volatile basic nitrogen (TVB-N) content in chilled mutton. Specifically, the sliding-windo...

Nitrogen Animals Odorants Deep Learning Volatile Organic Compounds Support Vector Machine Smell

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Machine Learning-Based Identification of Novel Exosome-Derived Metabolic Biomarkers for the Diagnosis of Systemic Lupus Erythematosus and Differentiation of Renal Involvement.

Current medical science Feb 28, 2025

OBJECTIVE: This study aims to investigate the exosome-derived metabolomics profiles in systemic lupus erythematosus (SLE), identify differential metabolites, and analyze their potential as diagnostic markers for SLE and lupus nephritis (LN).

Metabolomics Humans Diagnosis, Differential Machine Learning Female Exosomes Lupus Nephritis Case-Control Studies Biomarkers Lupus Erythematosus, Systemic Tandem Mass Spectrometry Adult ROC Curve Male Support Vector Machine Middle Aged

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AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Breast cancer prediction based on gene expression data using interpretable machine learning techniques.

Machine learning-based classification of spatially resolved diffuse reflectance and autofluorescence spectra acquired on human skin for actinic keratoses and skin carcinoma diagnostics aid.

Predictive modeling and optimization in dermatology: Machine learning for skin disease classification.

Deep Learning-Based Diagnostic Model for Parkinson's Disease Using Handwritten Spiral and Wave Images.

MRI radiomics based on machine learning in high-grade gliomas as a promising tool for prediction of CD44 expression and overall survival.

Diffusion-Weighted Imaging-Based Radiomics Features and Machine Learning Method to Predict the 90-Day Prognosis in Patients With Acute Ischemic Stroke.

Predicting responsiveness to fixed-dose methylene blue in adult patients with septic shock using interpretable machine learning: a retrospective study.

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.

Sliding-window enhanced olfactory visual images combined with deep learning to predict TVB-N content in chilled mutton.

Machine Learning-Based Identification of Novel Exosome-Derived Metabolic Biomarkers for the Diagnosis of Systemic Lupus Erythematosus and Differentiation of Renal Involvement.

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