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Support Vector Machine

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Discrimination of wheat gluten quality utilizing terahertz time-domain spectroscopy (THz-TDS).

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Wheat is an important food crop in the world, and wheat gluten quality is one of the important standards for judging the use of wheat. In this study, a combination of chemometric and machine learning methods based on THz-TDS were used to identify thr...

Assessment of simulated snoring sounds with artificial intelligence for the diagnosis of obstructive sleep apnea.

Sleep medicine
BACKGROUND: Performing simulated snoring (SS) is a commonly used method to evaluate the source of snoring in obstructive sleep apnea (OSA). SS sounds is considered as a potential biomarker for OSA. SS sounds can be easily recorded, which is a cost-ef...

Explainable machine learning models for predicting the acute toxicity of pesticides to sheepshead minnow (Cyprinodon variegatus).

The Science of the total environment
A quantitative structure-activity relationship (QSAR) study was conducted on 313 pesticides to predict their acute toxicity to Sheepshead minnow (Cyprinodon variegatus) by using DRAGON descriptors. Essentials accounting for a reliable model were all ...

Mobile Accelerometer Applications in Core Muscle Rehabilitation and Pre-Operative Assessment.

Sensors (Basel, Switzerland)
Individual physiotherapy is crucial in treating patients with various pain and health issues, and significantly impacts abdominal surgical outcomes and further medical problems. Recent technological and artificial intelligent advancements have equipp...

An interpretable (explainable) model based on machine learning and SHAP interpretation technique for mapping wind erosion hazard.

Environmental science and pollution research international
Soil erosion by wind poses a significant threat to various regions across the globe, such as drylands in the Middle East and Iran. Wind erosion hazard maps can assist in identifying the regions of highest wind erosion risk and are a valuable tool for...

The use of 4D data-independent acquisition-based proteomic analysis and machine learning to reveal potential biomarkers for stress levels.

Journal of bioinformatics and computational biology
Research suggests that individuals who experience prolonged exposure to stress may be at higher risk for developing psychological stress disorders. Currently, psychological stress is primarily evaluated by professional physicians using rating scales,...

Sex prediction through machine learning utilizing mandibular condyles, coronoid processes, and sigmoid notches features.

PloS one
Characteristics of the mandible structures have been relevant in anthropological and forensic studies for sex prediction. This study aims to evaluate the coronoid process, condyle, and sigmoid notch patterns in sex prediction through supervised machi...

Prediction of 12-month recurrence of pancreatic cancer using machine learning and prognostic factors.

BMC medical informatics and decision making
BACKGROUND AND AIM: Pancreatic cancer is lethal and prevalent among other cancer types. The recurrence of this tumor is high, especially in patients who did not receive adjuvant therapies. Early prediction of PC recurrence has a significant role in e...

Prediction model and technical and tactical decision analysis of women's badminton singles based on machine learning.

PloS one
In the Paris Olympic cycle, South Korean women's athlete An Se-young rose to the top of the 2023 BWF Olympic points with a win rate of 89.5%. With An Se-young as the subject, this paper aims to carry out technical and tactical analysis of women's bad...

Protocol to calculate and compare exact Shapley values for different kernels in support vector machine models using binary features.

STAR protocols
The Shapley value formalism from cooperative game theory was adapted to explain predictions of machine learning models. Here, we present a protocol to calculate and compare exact Shapley values for support vector machine models with commonly used ker...