AIMC Topic: Support Vector Machine

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A comparison of different machine learning classifiers in predicting xerostomia and sticky saliva due to head and neck radiotherapy using a multi-objective, multimodal radiomics model.

Biomedical physics & engineering express
. Although radiotherapy techniques are a primary treatment for head and neck cancer (HNC), they are still associated with substantial toxicity and side effects. Machine learning (ML) based radiomics models for predicting toxicity mostly rely on featu...

Using near-infrared hyperspectral imaging combined with machine learning to predict the components and the origin of Radix Paeoniae Rubra.

Analytical methods : advancing methods and applications
The efficacy and safety of drugs are closely related to the geographical origin and quality of the raw materials. This study focuses on using near-infrared hyperspectral imaging (NIR-HSI) combined with machine learning algorithms to construct content...

Machine learning-based analyzing earthquake-induced slope displacement.

PloS one
Accurately evaluating earthquake-induced slope displacement is a key factor for designing slopes that can effectively respond to seismic activity. This study evaluates the capabilities of various machine learning models, including artificial neural n...

Integrating machine learning for treatment decisions in anterior open bite orthodontic cases: A retrospective study.

Journal of the World federation of orthodontists
INTRODUCTION: This article explores the integration of machine learning (ML) algorithms to aid in treatment planning and extraction decisions for anterior open bite cases, leveraging demographic, clinical, and radiographic data to predict treatment o...

Real-Time Driver Drowsiness Detection Using Facial Analysis and Machine Learning Techniques.

Sensors (Basel, Switzerland)
Drowsy driving poses a significant challenge to road safety worldwide, contributing to thousands of accidents and fatalities annually. Despite advancements in driver drowsiness detection (DDD) systems, many existing methods face limitations such as i...

An intelligent decision-making system for embryo transfer in reproductive technology: a machine learning-based approach.

Systems biology in reproductive medicine
Infertility has emerged as a significant public health concern, with assisted reproductive technology (ART) is a last-resort treatment option. However, ART's efficacy is limited by significant financial cost and physical discomfort. The aim of this s...

Predictive models of clinical outcome of endovascular treatment for anterior circulation stroke using machine learning.

Journal of neuroscience methods
BACKGROUND AND PURPOSE: Mechanical Thrombectomy (MT) has recently become the standard of care for anterior circulation stroke with large vessel occlusion, but predictive factors of successful MT are still not clearly defined. To tailor treatment indi...

Establishing a preoperative predictive model for gallbladder adenoma and cholesterol polyps based on machine learning: a multicentre retrospective study.

World journal of surgical oncology
BACKGROUND: With the rising diagnostic rate of gallbladder polypoid lesions (GPLs), differentiating benign cholesterol polyps from gallbladder adenomas with a higher preoperative malignancy risk is crucial. This study aimed to establish a preoperativ...

Comparative Analysis of Machine Learning Algorithms Used for Translating Aptamer-Antigen Binding Kinetic Profiles to Diagnostic Decisions.

ACS sensors
Current approaches for classifying biosensor data in diagnostics rely on fixed decision thresholds based on receiver operating characteristic (ROC) curves, which can be limited in accuracy for complex and variable signals. To address these limitation...

An endoscopic ultrasound-based interpretable deep learning model and nomogram for distinguishing pancreatic neuroendocrine tumors from pancreatic cancer.

Scientific reports
To retrospectively develop and validate an interpretable deep learning model and nomogram utilizing endoscopic ultrasound (EUS) images to predict pancreatic neuroendocrine tumors (PNETs). Following confirmation via pathological examination, a retrosp...