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Support Vector Machine

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Accurate prediction of colorectal cancer diagnosis using machine learning based on immunohistochemistry pathological images.

Scientific reports
Colorectal cancer (CRC) ranks as the third most prevalent tumor and the second leading cause of mortality. Early and accurate diagnosis holds significant importance in enhancing patient treatment and prognosis. Machine learning technology and bioinfo...

Machine learning and regression in the management of runoff in bauxite mines under rehabilitation.

Environmental science and pollution research international
Accurate and reliable forecasting of monthly runoff considering several years of rehabilitation helps in planning and managing the water resources system of bauxite mining areas. A combination of linear regression models and artificial intelligence w...

Diabetic retinopathy detection via deep learning based dual features integrated classification model.

Technology and health care : official journal of the European Society for Engineering and Medicine
BackgroundThe primary recognition of diabetic retinopathy (DR) is a pivotal requirement to prevent blindness and vision impairment. This deadly condition is identified by highly qualified professionals by examining colored retinal images.ObjectiveThe...

The development of classification-based machine-learning models for the toxicity assessment of chemicals associated with plastic packaging.

Journal of hazardous materials
Assessing chemical toxicity in materials like plastic packaging is critical to safeguarding public health. This study presents the development of classification-based machine learning models to predict the toxicity of chemicals associated with plasti...

Assessing the performance of machine learning algorithms for analyzing land use changes in the Hyrcanian forests of Iran.

Environmental science and pollution research international
Land use changes are of critical importance in understanding and managing environmental sustainability and resource utilization. Machine learning algorithms (MLAs) have emerged as powerful tools for analyzing and predicting land use changes, offering...

XGBoost as a reliable machine learning tool for predicting ancestry using autosomal STR profiles - Proof of method.

Forensic science international. Genetics
The aim of this study was to test the validity of a predictive model of ancestry affiliation based on Short Tandem Repeat (STR) profiles. Frequencies of 29 genetic markers from the Promega website for four distinct population groups (African American...

Relationship of Community Mobility, Vital Space, and Faller Status in Older Adults.

Sensors (Basel, Switzerland)
UNLABELLED: Community mobility, encompassing both active (e.g., walking) and passive (e.g., driving) transport, plays a crucial role in maintaining autonomy and social interaction among older adults. This study aimed to quantify community mobility in...

Predicting the time to get back to work using statistical models and machine learning approaches.

BMC medical research methodology
BACKGROUND: Whether machine learning approaches are superior to classical statistical models for survival analyses, especially in the case of lack of proportionality, is unknown.

Mapping surface soil organic carbon density of cultivated land using machine learning in Zhengzhou.

Environmental geochemistry and health
Research on soil organic carbon (SOC) is crucial for improving soil carbon sinks and achieving the "double-carbon" goal. This study introduces ten auxiliary variables based on the data from a 2021 land quality survey in Zhengzhou and a multi-objectiv...