AIMC Topic: Support Vector Machine

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Prediction of Chemotherapy Response of Osteosarcoma Using Baseline F-FDG Textural Features Machine Learning Approaches with PCA.

Contrast media & molecular imaging
PURPOSE: Patients with high-grade osteosarcoma undergo several chemotherapy cycles before surgical intervention. Response to chemotherapy, however, is affected by intratumor heterogeneity. In this study, we assessed the ability of a machine learning ...

A Novel Approach for Multi-Lead ECG Classification Using DL-CCANet and TL-CCANet.

Sensors (Basel, Switzerland)
Cardiovascular disease (CVD) has become one of the most serious diseases that threaten human health. Over the past decades, over 150 million humans have died of CVDs. Hence, timely prediction of CVDs is especially important. Currently, deep learning ...

IoT with cloud based lung cancer diagnosis model using optimal support vector machine.

Health care management science
In the last decade, exponential growth of Internet of Things (IoT) and cloud computing takes the healthcare services to the next level. At the same time, lung cancer is identified as a dangerous disease which increases the global mortality rate annua...

Is it possible to detect cerebral dominance via EEG signals by using deep learning?

Medical hypotheses
Each brain hemisphere is dominant for certain functions such as speech. The determination of speech laterality prior to surgery is of paramount importance for accurate risk prediction. In this study, we aimed to determine speech laterality via EEG si...

Machine Learning Approaches for Automated Lesion Detection in Microwave Breast Imaging Clinical Data.

Scientific reports
Breast lesion detection employing state of the art microwave systems provide a safe, non-ionizing technique that can differentiate healthy and non-healthy tissues by exploiting their dielectric properties. In this paper, a microwave apparatus for bre...

Pan-Renal Cell Carcinoma classification and survival prediction from histopathology images using deep learning.

Scientific reports
Histopathological images contain morphological markers of disease progression that have diagnostic and predictive values. In this study, we demonstrate how deep learning framework can be used for an automatic classification of Renal Cell Carcinoma (R...

Accurate prediction of potential druggable proteins based on genetic algorithm and Bagging-SVM ensemble classifier.

Artificial intelligence in medicine
Discovering and accurately locating drug targets is of great significance for the research and development of new drugs. As a different approach to traditional drug development, the machine learning algorithm is used to predict the drug target by min...

Clinically Applicable Deep Learning Algorithm Using Quantitative Proteomic Data.

Journal of proteome research
Deep learning (DL), a type of machine learning approach, is a powerful tool for analyzing large sets of data that are derived from biomedical sciences. However, it remains unknown whether DL is suitable for identifying contributing factors, such as b...

An Ensemble Classifier to Predict Protein-Protein Interactions by Combining PSSM-based Evolutionary Information with Local Binary Pattern Model.

International journal of molecular sciences
Protein plays a critical role in the regulation of biological cell functions. Among them, whether proteins interact with each other has become a fundamental problem, because proteins usually perform their functions by interacting with other proteins....

Cervical Cancer Identification with Synthetic Minority Oversampling Technique and PCA Analysis using Random Forest Classifier.

Journal of medical systems
Cervical cancer is the fourth most communal malignant disease amongst women worldwide. In maximum circumstances, cervical cancer indications are not perceptible at its initial stages. There are a proportion of features that intensify the threat of em...