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Support Vector Machine

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Olfactory analysis of oolong tea sensory quality using composite nano-colorimetric sensor array.

Food research international (Ottawa, Ont.)
Chinese oolong tea is famous for its rich and diverse aromas, which is an important indicator for sensor quality evaluation. To accurately and rapidly evaluate sensory quality, a novel colorimetric sensor array (CSA) was developed to detect volatile ...

Optimizing cancer diagnosis: A hybrid approach of genetic operators and Sinh Cosh Optimizer for tumor identification and feature gene selection.

Computers in biology and medicine
The identification of tumors through gene analysis in microarray data is a pivotal area of research in artificial intelligence and bioinformatics. This task is challenging due to the large number of genes relative to the limited number of observation...

Detection of Pilots' Psychological Workload during Turning Phases Using EEG Characteristics.

Sensors (Basel, Switzerland)
Pilot behavior is crucial for aviation safety. This study aims to investigate the EEG characteristics of pilots, refine training assessment methodologies, and bolster flight safety measures. The collected EEG signals underwent initial preprocessing. ...

Non-invasive prediction of axillary lymph node dissection exemption in breast cancer patients post-neoadjuvant therapy: A radiomics and deep learning analysis on longitudinal DCE-MRI data.

Breast (Edinburgh, Scotland)
PURPOSE: In breast cancer (BC) patients with clinical axillary lymph node metastasis (cN+) undergoing neoadjuvant therapy (NAT), precise axillary lymph node (ALN) assessment dictates therapeutic strategy. There is a critical demand for a precise meth...

Multiview learning with twin parametric margin SVM.

Neural networks : the official journal of the International Neural Network Society
Multiview learning (MVL) seeks to leverage the benefits of diverse perspectives to complement each other, effectively extracting and utilizing the latent information within the dataset. Several twin support vector machine-based MVL (MvTSVM) models ha...

Artificial intelligence prediction of In-Hospital mortality in patients with dementia: A multi-center study.

International journal of medical informatics
BACKGROUND: Prediction of mortality is very important for care planning in hospitalized patients with dementia and artificial intelligence has the potential to serve as a solution; however, this issue remains unclear. Thus, this study was conducted t...

Exploring the Impact of Fine-Tuning the Wav2vec2 Model in Database-Independent Detection of Dysarthric Speech.

IEEE journal of biomedical and health informatics
Many acoustic features and machine learning models have been studied to build automatic detection systems to distinguish dysarthric speech from healthy speech. These systems can help to improve the reliability of diagnosis. However, speech recorded f...

Predicting Metformin Efficacy in Improving Insulin Sensitivity Among Women With Polycystic Ovary Syndrome and Insulin Resistance: A Machine Learning Study.

Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists
OBJECTIVE: Metformin is clinically effective in treating polycystic ovary syndrome (PCOS) with insulin resistance (IR), while its efficacy varies among individuals. This study aims to develop a machine learning model to predict the efficacy of metfor...

Machine learning-enabled detection of attention-deficit/hyperactivity disorder with multimodal physiological data: a case-control study.

BMC psychiatry
BACKGROUND: Attention-Deficit/Hyperactivity Disorder (ADHD) is a multifaceted neurodevelopmental psychiatric condition that typically emerges during childhood but often persists into adulthood, significantly impacting individuals' functioning, relati...