AIMC Topic: Support Vector Machine

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Photonic platform coupled with machine learning algorithms to detect pyrolysis products of crack cocaine in saliva: A proof-of-concept animal study.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Dec 18, 2024
The non-invasive detection of crack/cocaine and other bioactive compounds from its pyrolysis in saliva can provide an alternative for drug analysis in forensic toxicology. Therefore, a highly sensitive, fast, reagent-free, and sustainable approach wi...
Photons Crack Cocaine Principal Component Analysis Saliva Proof of Concept Study Pyrolysis Rats Support Vector Machine Machine Learning Spectroscopy, Fourier Transform Infrared Animals Male
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Predicting cyclins based on key features and machine learning methods.

Methods (San Diego, Calif.) Dec 18, 2024
Cyclins are a group of proteins that regulate the cell cycle process by modulating various stages of cell division to ensure correct cell proliferation, differentiation, and apoptosis. Research on cyclins is crucial for understanding the biological f...
Humans Machine Learning Support Vector Machine Cyclins
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Unravelling intubation challenges: a machine learning approach incorporating multiple predictive parameters.

BMC anesthesiology Dec 18, 2024
BACKGROUND: To protect patients during anesthesia, difficult airway management is a serious issue that needs to be carefully planned for and carried out. Machine learning prediction tools have recently become increasingly common in medicine, frequent...
Humans Female Adult Machine Learning Algorithms Intubation, Intratracheal Support Vector Machine Decision Trees Cross-Sectional Studies Iran Male Airway Management Middle Aged
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An explainable analysis of diabetes mellitus using statistical and artificial intelligence techniques.

BMC medical informatics and decision making Dec 18, 2024
BACKGROUND: Diabetes mellitus (DM) is a chronic disease prevalent worldwide, requiring a multifaceted analytical approach to improve early detection and subsequent mitigation of morbidity and mortality rates. This research aimed to develop an explain...
Support Vector Machine Models, Statistical Male Middle Aged Diabetes Mellitus Humans Neural Networks, Computer Aged Artificial Intelligence Adult Female
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Machine learning models predict the progression of long-term renal insufficiency in patients with renal cancer after radical nephrectomy.

BMC nephrology Dec 18, 2024
BACKGROUND: Chronic Kidney Disease (CKD) is a common severe complication after radical nephrectomy in patients with renal cancer. The timely and accurate prediction of the long-term progression of renal function post-surgery is crucial for early inte...
Kidney Neoplasms Carcinoma, Renal Cell Nephrectomy Disease Progression Renal Insufficiency, Chronic Support Vector Machine Machine Learning Retrospective Studies Female Middle Aged Postoperative Complications Aged Male Humans
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Auxiliary identification of depression patients using interpretable machine learning models based on heart rate variability: a retrospective study.

BMC psychiatry Dec 18, 2024
OBJECTIVE: Depression has emerged as a global public health concern with high incidence and disability rates, which are timely imperative to identify and intervene in clinical practice. The objective of this study was to explore the association betwe...
Humans Adult Male Middle Aged Depression Machine Learning Retrospective Studies Female Support Vector Machine Heart Rate Depressive Disorder
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Predicting maternal risk level using machine learning models.

BMC pregnancy and childbirth Dec 18, 2024
BACKGROUND: Maternal morbidity and mortality remain critical health concerns globally. As a result, reducing the maternal mortality ratio (MMR) is part of goal 3 in the global sustainable development goals (SDGs), and previously, it was an important ...
Bayes Theorem Oman Maternal Mortality Pregnancy Female Humans Adult Neural Networks, Computer Machine Learning Risk Assessment Algorithms Logistic Models Support Vector Machine Principal Component Analysis
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Improving the Performance of Electrotactile Brain-Computer Interface Using Machine Learning Methods on Multi-Channel Features of Somatosensory Event-Related Potentials.

Sensors (Basel, Switzerland) Dec 17, 2024
Traditional tactile brain-computer interfaces (BCIs), particularly those based on steady-state somatosensory-evoked potentials, face challenges such as lower accuracy, reduced bit rates, and the need for spatially distant stimulation points. In contr...
Adult Humans Male Evoked Potentials, Somatosensory Machine Learning Signal Processing, Computer-Assisted Support Vector Machine Algorithms Electroencephalography Brain-Computer Interfaces Female Touch Young Adult
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Impaired interhemispheric synchrony in patients with iridocyclitis and classification using machine learning: an fMRI study.

Frontiers in immunology Dec 16, 2024
BACKGROUND: This study examined the interhemispheric integration function pattern in patients with iridocyclitis utilizing the voxel-mirrored homotopic connectivity (VMHC) technique. Additionally, we investigated the ability of VMHC results to distin...
Female Iridocyclitis Humans Middle Aged Brain Mapping Adult Support Vector Machine Machine Learning Male Magnetic Resonance Imaging Brain
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Anxiety in aquatics: Leveraging machine learning models to predict adult zebrafish behavior.

Neuroscience Dec 13, 2024
Accurate analysis of anxiety behaviors in animal models is pivotal for advancing neuroscience research and drug discovery. This study compares the potential of DeepLabCut, ZebraLab, and machine learning models to analyze anxiety-related behaviors in ...
Support Vector Machine Disease Models, Animal Machine Learning Zebrafish Animals Behavior, Animal Anxiety
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