AI Medical Compendium Topic:
Support Vector Machine

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mmWave-RM: A Respiration Monitoring and Pattern Classification System Based on mmWave Radar.

Sensors (Basel, Switzerland)
Breathing is one of the body's most basic functions and abnormal breathing can indicate underlying cardiopulmonary problems. Monitoring respiratory abnormalities can help with early detection and reduce the risk of cardiopulmonary diseases. In this s...

Rapid detection of lung cancer based on serum Raman spectroscopy and a support vector machine: a case-control study.

BMC cancer
BACKGROUND: Early screening and detection of lung cancer is essential for the diagnosis and prognosis of the disease. In this paper, we investigated the feasibility of serum Raman spectroscopy for rapid lung cancer screening.

Matrix metalloproteinase 9 expression and glioblastoma survival prediction using machine learning on digital pathological images.

Scientific reports
This study aimed to apply pathomics to predict Matrix metalloproteinase 9 (MMP9) expression in glioblastoma (GBM) and investigate the underlying molecular mechanisms associated with pathomics. Here, we included 127 GBM patients, 78 of whom were rando...

Power spectral density-based resting-state EEG classification of first-episode psychosis.

Scientific reports
Historically, the analysis of stimulus-dependent time-frequency patterns has been the cornerstone of most electroencephalography (EEG) studies. The abnormal oscillations in high-frequency waves associated with psychotic disorders during sensory and c...

Using Pupil Diameter for Psychological Resilience Assessment in Medical Students Based on SVM and SHAP Model.

IEEE journal of biomedical and health informatics
Effectively assessing psychological resilience for medical students is vital for identifying at-risk individuals and developing tailored interventions. At present, few studies have combined physiological indexes of the human body and machine learning...

Prediction and Interpretation Microglia Cytotoxicity by Machine Learning.

Journal of chemical information and modeling
Ameliorating microglia-mediated neuroinflammation is a crucial strategy in developing new drugs for neurodegenerative diseases. Plant compounds are an important screening target for the discovery of drugs for the treatment of neurodegenerative diseas...

Predicting efficacy of antiseizure medication treatment with machine learning algorithms in North Indian population.

Epilepsy research
PURPOSE: This study aimed to develop a classifier using supervised machine learning to effectively assess the impact of clinical, demographical, and biochemical factors in accurately predicting the antiseizure medications (ASMs) treatment response in...

Scaffold-Hopped Compound Identification by Ligand-Based Approaches with a Prospective Affinity Test.

Journal of chemical information and modeling
Scaffold-hopped (SH) compounds are bioactive compounds structurally different from known active compounds. Identifying SH compounds in the ligand-based approaches has been a central issue in medicinal chemistry, and various molecular representations ...

Efficient Generalized Electroencephalography-Based Drowsiness Detection Approach with Minimal Electrodes.

Sensors (Basel, Switzerland)
Drowsiness is a main factor for various costly defects, even fatal accidents in areas such as construction, transportation, industry and medicine, due to the lack of monitoring vigilance in the mentioned areas. The implementation of a drowsiness dete...

APLpred: A machine learning-based tool for accurate prediction and characterization of asparagine peptide lyases using sequence-derived optimal features.

Methods (San Diego, Calif.)
Asparagine peptide lyase (APL) is among the seven groups of proteases, also known as proteolytic enzymes, which are classified according to their catalytic residue. APLs are synthesized as precursors or propeptides that undergo self-cleavage through ...