AIMC Topic: Support Vector Machine

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Natural language processing and machine learning algorithm to identify brain MRI reports with acute ischemic stroke.

PloS one
BACKGROUND AND PURPOSE: This project assessed performance of natural language processing (NLP) and machine learning (ML) algorithms for classification of brain MRI radiology reports into acute ischemic stroke (AIS) and non-AIS phenotypes.

An Enhancement of Deep Learning Algorithm for Brain Tumor Segmentation Using Kernel Based CNN with M-SVM.

Journal of medical systems
The brain tumor can be created by uncontrollable increase of abnormal cells in tissue of brain and it has two kinds of tumors: one is benign and another one is malignant tumor. The benign brain tumor does not affect the adjacent normal and healthy ti...

Classification of Cyclooxygenase-2 Inhibitors Using Support Vector Machine and Random Forest Methods.

Journal of chemical information and modeling
This work reports the classification study conducted on the biggest COX-2 inhibitor data set so far. Using 2925 diverse COX-2 inhibitors collected from 168 pieces of literature, we applied machine learning methods, support vector machine (SVM) and ra...

iEnhancer-5Step: Identifying enhancers using hidden information of DNA sequences via Chou's 5-step rule and word embedding.

Analytical biochemistry
An enhancer is a short (50-1500bp) region of DNA that plays an important role in gene expression and the production of RNA and proteins. Genetic variation in enhancers has been linked to many human diseases, such as cancer, disorder or inflammatory b...

Multiple Machine Learning Comparisons of HIV Cell-based and Reverse Transcriptase Data Sets.

Molecular pharmaceutics
The human immunodeficiency virus (HIV) causes over a million deaths every year and has a huge economic impact in many countries. The first class of drugs approved were nucleoside reverse transcriptase inhibitors. A newer generation of reverse transcr...

Prediction of apoptosis protein subcellular localization via heterogeneous features and hierarchical extreme learning machine.

SAR and QSAR in environmental research
Apoptosis is a fundamental process controlling normal tissue homeostasis by regulating a balance between cell proliferation and death. Predicting the subcellular location of apoptosis proteins is very helpful for understanding the mechanism of progra...

A Novel Hybrid Feature Extraction Model for Classification on Pulmonary Nodules.

Asian Pacific journal of cancer prevention : APJCP
In this paper an improved Computer Aided Design system can offer a second opinion to radiologists on early diagnosis of pulmonary nodules on CT (Computer Tomography) images. A Deep Convolutional Neural Network (DCNN) method is used for feature extrac...

Chat Analysis Triage Tool: Differentiating contact-driven vs. fantasy-driven child sex offenders.

Forensic science international
Investigating crimes against children, specifically sexual solicitations, are complicated because not all offenders are contact-driven, meaning they want to meet the minor for sex in the physical world; instead, some offenders are fantasy-driven, in ...

Bone Marrow Cells Detection: A Technique for the Microscopic Image Analysis.

Journal of medical systems
In the detection of myeloproliferative, the number of cells in each type of bone marrow cells (BMC) is an important parameter for the evaluation. In this study, we propose a new counting method, which consists of three modules including localization,...

Deep Learning-Based Framework for Identification of Glioblastoma Tumor using Hyperspectral Images of Human Brain.

Sensors (Basel, Switzerland)
The main goal of brain cancer surgery is to perform an accurate resection of the tumor, preserving as much normal brain tissue as possible for the patient. The development of a non-contact and label-free method to provide reliable support for tumor r...