AIMC Topic: Support Vector Machine

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Optimizing fractionation schedules for de-escalation radiotherapy in head and neck cancers using deep reinforcement learning.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Mar 14, 2025
PURPOSE: Patients with locally-advanced head and neck squamous cell carcinomas (HNSCCs), particularly those related to human papillomavirus (HPV), often achieve good locoregional control (LRC), yet they suffer significant toxicities from standard che...
Reinforcement Machine Learning Head and Neck Neoplasms Support Vector Machine Radiotherapy Planning, Computer-Assisted Dose Fractionation, Radiation Humans Deep Learning Squamous Cell Carcinoma of Head and Neck
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Integration of intratumoral and peritumoral CT radiomic features with machine learning algorithms for predicting induction therapy response in locally advanced non-small cell lung cancer.

BMC cancer Mar 13, 2025
OBJECTIVES: To extract intratumoral, peritumoral, and integrated intratumoral-peritumoral CT radiomic features, develop multi-source radiomic models using various machine learning algorithms to identify the optimal model, and integrate clinical facto...
Carcinoma, Non-Small-Cell Lung Tumor Burden Induction Chemotherapy Lung Neoplasms Nomograms Treatment Outcome Support Vector Machine Radiomics Male Middle Aged Tomography, X-Ray Computed Humans Female Machine Learning Aged Algorithms Adult Retrospective Studies
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Biological age prediction and NAFLD risk assessment: a machine learning model based on a multicenter population in Nanchang, Jiangxi, China.

BMC gastroenterology Mar 13, 2025
BACKGROUND: The objective was to develop a biological age prediction model (NC-BA) for the Chinese population to enrich the relevant studies in this population. And to investigate the association between accelerated age and NAFLD.
Humans Machine Learning Biomarkers Female Aged Support Vector Machine Age Factors Adult Middle Aged Non-alcoholic Fatty Liver Disease Male Risk Assessment Linear Models Aging China Nutrition Surveys
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ELTIRADS framework for thyroid nodule classification integrating elastography, TIRADS, and radiomics with interpretable machine learning.

Scientific reports Mar 13, 2025
Early detection of malignant thyroid nodules is crucial for effective treatment, but traditional diagnostic methods face challenges such as variability in expert opinions and limited integration of advanced imaging techniques. This prospective cohort...
Support Vector Machine Biopsy, Fine-Needle Elasticity Imaging Techniques Humans Male Aged Machine Learning Middle Aged Adult Prospective Studies Thyroid Neoplasms Radiomics Female Thyroid Nodule
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Enhanced personalized prediction of baseball-related upper extremity injuries through novel features and explainable artificial intelligence.

Journal of sports sciences Mar 12, 2025
Upper extremity injuries in baseball players demand advanced prevention. Our study analyzed clinical features using machine learning techniques to provide precise and individualized injury risk assessment and prediction. We recruited 98 baseball play...
Support Vector Machine Rotation Upper Extremity Baseball Male Risk Assessment Logistic Models Athletic Injuries Humans Artificial Intelligence Machine Learning Young Adult Adult
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Altered resting-state brain activity in patients with major depression disorder and bipolar disorder: A regional homogeneity analysis.

Journal of affective disorders Mar 11, 2025
BACKGROUND: Major Depressive Disorder (MDD) and Bipolar Disorder (BD) exhibit overlapping depressive symptoms, complicating their differentiation in clinical practice. Traditional neuroimaging studies have focused on specific regions of interest, but...
Brain Mapping Diagnosis, Differential Bipolar Disorder Support Vector Machine Magnetic Resonance Imaging Humans Adult Brain Male Female Middle Aged Depressive Disorder, Major
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Mapping acrylamide content in potato chips using near-infrared hyperspectral imaging and chemometrics.

Food chemistry Mar 9, 2025
This study investigated the potential of near-infrared hyperspectral imaging (NIR-HSI) for the prediction of acrylamide content in potato chips. A total of 300 tubers from two potato varieties (Agria and Jaerla) grown in two seasons and processed und...
Spectroscopy, Near-Infrared Cooking Food Contamination Support Vector Machine Least-Squares Analysis Acrylamide Hyperspectral Imaging Plant Tubers Solanum tuberosum Chemometrics
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Comparison of Deep Learning and Traditional Machine Learning Models for Predicting Mild Cognitive Impairment Using Plasma Proteomic Biomarkers.

International journal of molecular sciences Mar 8, 2025
Mild cognitive impairment (MCI) is a clinical condition characterized by a decline in cognitive ability and progression of cognitive impairment. It is often considered a transitional stage between normal aging and Alzheimer's disease (AD). This study...
Deep Learning Cognitive Dysfunction Aged, 80 and over Proteomics Support Vector Machine Machine Learning Male Humans Middle Aged Biomarkers Female Aged
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Predicting surface soil pH spatial distribution based on three machine learning methods: a case study of Heilongjiang Province.

Environmental monitoring and assessment Mar 8, 2025
Comprehensive and accurate acquisition of surface soil pH spatial distribution information is essential for monitoring soil degradation and providing scientific guidance for agricultural practices. This study focused on Heilongjiang Province in China...
Environmental Monitoring Support Vector Machine Models, Chemical Hydrogen-Ion Concentration Machine Learning Soil China
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The Application of Machine Learning Models to Predict Stillbirths.

Medicina (Kaunas, Lithuania) Mar 7, 2025
: This study aims to evaluate the predictive value of comprehensive data obtained in obstetric clinics for the detection of stillbirth and the predictive ability set of machine learning models for stillbirth. : The study retrospectively included all ...
Support Vector Machine Pregnancy Stillbirth Female Adult Humans Logistic Models Machine Learning Retrospective Studies
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