AIMC Topic: Support Vector Machine

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Development of a machine learning-based real-time location system to streamline acute endovascular intervention in acute stroke: a proof-of-concept study.

Journal of neurointerventional surgery Aug 23, 2021
BACKGROUND: Delivery of acute stroke endovascular intervention can be challenging because it requires complex coordination of patient and staff across many different locations. In this proof-of-concept paper we (a) examine whether WiFi fingerprinting...
Humans Support Vector Machine Stroke Machine Learning Software Algorithms
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iBitter-Fuse: A Novel Sequence-Based Bitter Peptide Predictor by Fusing Multi-View Features.

International journal of molecular sciences Aug 19, 2021
Accurate identification of bitter peptides is of great importance for better understanding their biochemical and biophysical properties. To date, machine learning-based methods have become effective approaches for providing a good avenue for identify...
Benchmarking Taste Predictive Value of Tests Peptide Fragments Humans Machine Learning Software Algorithms Support Vector Machine
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A Tri-Stage Wrapper-Filter Feature Selection Framework for Disease Classification.

Sensors (Basel, Switzerland) Aug 18, 2021
In machine learning and data science, feature selection is considered as a crucial step of data preprocessing. When we directly apply the raw data for classification or clustering purposes, sometimes we observe that the learning algorithms do not per...
Support Vector Machine Cluster Analysis Bayes Theorem Algorithms Humans Male Machine Learning
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Automated detection and explainability of pathological gait patterns using a one-class support vector machine trained on inertial measurement unit based gait data.

Clinical biomechanics (Bristol, Avon) Aug 17, 2021
BACKGROUND: Machine learning approaches for the classification of pathological gait based on kinematic data, e.g. derived from inertial sensors, are commonly used in terms of a multi-class classification problem. However, there is a lack of research ...
Arthroplasty, Replacement, Hip Biomechanical Phenomena Humans Support Vector Machine Gait Machine Learning
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Predicting Antimalarial Activity in Natural Products Using Pretrained Bidirectional Encoder Representations from Transformers.

Journal of chemical information and modeling Aug 16, 2021
Malaria is a threatening disease that has claimed many lives and has a high prevalence rate annually. Through the past decade, there have been many studies to uncover effective antimalarial compounds to combat this disease. Alongside chemically synth...
Support Vector Machine Biological Products Machine Learning Antimalarials Algorithms
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Random walks on B distributed resting-state functional connectivity to identify Alzheimer's disease and Mild Cognitive Impairment.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology Aug 16, 2021
OBJECTIVE: Resting-state functional connectivity reveals a promising way for the early detection of dementia. This study proposes a novel method to accurately classify Healthy Controls, Early Mild Cognitive Impairment, Late Mild Cognitive Impairment,...
Humans Algorithms Databases, Factual Brain Female Magnetic Resonance Imaging Alzheimer Disease Rest Nerve Net Male Cognitive Dysfunction Support Vector Machine Aged Aged, 80 and over
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An Improved Stacked Autoencoder for Metabolomic Data Classification.

Computational intelligence and neuroscience Aug 15, 2021
Naru3 (NR) is a traditional Mongolian medicine with high clinical efficacy and low incidence of side effects. Metabolomics is an approach that can facilitate the development of traditional drugs. However, metabolomic data have a high throughput, spar...
Mice Support Vector Machine Algorithms Metabolomics Animals
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Classification Framework for Healthy Hairs and Alopecia Areata: A Machine Learning (ML) Approach.

Computational and mathematical methods in medicine Aug 14, 2021
Alopecia areata is defined as an autoimmune disorder that results in hair loss. The latest worldwide statistics have exhibited that alopecia areata has a prevalence of 1 in 1000 and has an incidence of 2%. Machine learning techniques have demonstrate...
Optical Imaging Humans Support Vector Machine Hair Hair Color Algorithms Image Interpretation, Computer-Assisted Alopecia Areata Machine Learning Databases, Factual Computational Biology
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Artificial intelligence to improve efficiency of administration of gross motor function assessment in children with cerebral palsy.

Developmental medicine and child neurology Aug 13, 2021
AIM: To create a reduced version of the 66-item Gross Motor Function Measure (rGMFM-66) using innovative artificial intelligence methods to improve efficiency of administration of the GMFM-66.
Humans Motor Skills Support Vector Machine Cerebral Palsy Female Neural Networks, Computer Machine Learning Artificial Intelligence Adolescent Male Prospective Studies Retrospective Studies Child, Preschool Severity of Illness Index Child
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Linear and non-linear feature extraction from rat electrocorticograms for seizure detection by support vector machine.

Biomedizinische Technik. Biomedical engineering Aug 12, 2021
Seizures, the main symptom of epilepsy, are provoked due to a neurological disorder that underlies the disease. The accurate detection of seizures is a crucial step in any procedure of treatment. In the present study, electrocorticogram (ECoG) signal...
Algorithms Animals Epilepsy Seizures Signal Processing, Computer-Assisted Rats Support Vector Machine Electroencephalography
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