AIMC Topic: Support Vector Machine

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Development of a Prediction Model for Demolition Waste Generation Using a Random Forest Algorithm Based on Small DataSets.

International journal of environmental research and public health Sep 24, 2020
Recently, artificial intelligence (AI) technologies have been employed to predict construction and demolition (C&D) waste generation. However, most studies have used machine learning models with continuous data input variables, applying algorithms, s...
Construction Industry Solid Waste Algorithms Support Vector Machine Neural Networks, Computer Artificial Intelligence Machine Learning
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Multipose Face Recognition-Based Combined Adaptive Deep Learning Vector Quantization.

Computational intelligence and neuroscience Sep 24, 2020
Multipose face recognition system is one of the recent challenges faced by the researchers interested in security applications. Different researches have been introduced discussing the accuracy improvement of multipose face recognition through enhanc...
Neural Networks, Computer Reproducibility of Results Deep Learning Support Vector Machine Facial Recognition
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Discovery of Dual FGFR4 and EGFR Inhibitors by Machine Learning and Biological Evaluation.

Journal of chemical information and modeling Sep 23, 2020
Kinase inhibitors are widely used in antitumor research, but there are still many problems such as drug resistance and off-target toxicity. A more suitable solution is to design a multitarget inhibitor with certain selectivity. Herein, computational ...
Support Vector Machine Quantitative Structure-Activity Relationship ErbB Receptors Machine Learning Molecular Docking Simulation
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A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein Trimers.

Molecules (Basel, Switzerland) Sep 23, 2020
Study of interface residue pairs is important for understanding the interactions between monomers inside a trimer protein-protein complex. We developed a two-layer support vector machine (SVM) ensemble-classifier that considers physicochemical and ge...
Support Vector Machine Proteins Protein Structure, Quaternary Protein Multimerization Computational Biology
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Identifying Heat Shock Protein Families from Imbalanced Data by Using Combined Features.

Computational and mathematical methods in medicine Sep 23, 2020
Heat shock proteins (HSPs) are ubiquitous in living organisms. HSPs are an essential component for cell growth and survival; the main function of HSPs is controlling the folding and unfolding process of proteins. According to molecular function and m...
Dipeptides Mathematical Concepts Support Vector Machine Animals Humans Amino Acid Sequence Amino Acids Computational Biology Databases, Protein Algorithms Heat-Shock Proteins
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Classification of normal sinus rhythm, abnormal arrhythmia and congestive heart failure ECG signals using LSTM and hybrid CNN-SVM deep neural networks.

Computer methods in biomechanics and biomedical engineering Sep 21, 2020
Effective monitoring of heart patients according to heart signals can save a huge amount of life. In the last decade, the classification and prediction of heart diseases according to ECG signals has gained great importance for patients and doctors. I...
Heart Failure Arrhythmias, Cardiac Electrocardiography Support Vector Machine Signal Processing, Computer-Assisted Male Neural Networks, Computer Middle Aged Algorithms Humans Young Adult Adult Female
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Comparison of Scaling Methods to Obtain Calibrated Probabilities of Activity for Protein-Ligand Predictions.

Journal of chemical information and modeling Sep 21, 2020
In the context of bioactivity prediction, the question of how to calibrate a score produced by a machine learning method into a probability of binding to a protein target is not yet satisfactorily addressed. In this study, we compared the performance...
Bayes Theorem Machine Learning Ligands Support Vector Machine Probability
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Development of a Robust Multi-Scale Featured Local Binary Pattern for Improved Facial Expression Recognition.

Sensors (Basel, Switzerland) Sep 21, 2020
Compelling facial expression recognition (FER) processes have been utilized in very successful fields like computer vision, robotics, artificial intelligence, and dynamic texture recognition. However, the FER's critical problem with traditional local...
Humans Automated Facial Recognition Algorithms Facial Expression Support Vector Machine
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Using Chou's 5-steps rule to identify N-methyladenine sites by ensemble learning combined with multiple feature extraction methods.

Journal of biomolecular structure & dynamics Sep 18, 2020
-methyladenine (m6A), a type of modification mostly affecting the downstream biological functions and determining the levels of gene expression, is mediated by the methylation of adenine in nucleic acids. It is also a key factor for influencing biolo...
Mice Machine Learning Computational Biology Humans Algorithms Bayes Theorem Support Vector Machine Animals Adenine
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Prediction of early recurrence of hepatocellular carcinoma after resection using digital pathology images assessed by machine learning.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc Sep 18, 2020
Hepatocellular carcinoma (HCC) is a representative primary liver cancer caused by long-term and repetitive liver injury. Surgical resection is generally selected as the radical cure treatment. Because the early recurrence of HCC after resection is as...
Aged, 80 and over Adult Male Female Aged Carcinoma, Hepatocellular Support Vector Machine Neoplasm Recurrence, Local Middle Aged Liver Neoplasms Prognosis Retrospective Studies Humans Hepatectomy
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