AIMC Topic: Support Vector Machine

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Regional Multi-View Learning for Cardiac Motion Analysis: Application to Identification of Dilated Cardiomyopathy Patients.

IEEE transactions on bio-medical engineering
OBJECTIVE: The aim of this paper is to describe an automated diagnostic pipeline that uses as input only ultrasound (US) data, but is at the same time informed by a training database of multimodal magnetic resonance (MR) and US image data.

A convolutional route to abbreviation disambiguation in clinical text.

Journal of biomedical informatics
OBJECTIVE: Abbreviations sense disambiguation is a special case of word sense disambiguation. Machine learning methods based on neural networks showed promising results for word sense disambiguation (Festag and Spreckelsen, 2017) [1] and, here we ass...

Risk prediction using natural language processing of electronic mental health records in an inpatient forensic psychiatry setting.

Journal of biomedical informatics
OBJECTIVE: Instruments rating risk of harm to self and others are widely used in inpatient forensic psychiatry settings. A potential alternate or supplementary means of risk prediction is from the automated analysis of case notes in Electronic Health...

A New Method for Recognizing Cytokines Based on Feature Combination and a Support Vector Machine Classifier.

Molecules (Basel, Switzerland)
Research on cytokine recognition is of great significance in the medical field due to the fact cytokines benefit the diagnosis and treatment of diseases, but the current methods for cytokine recognition have many shortcomings, such as low sensitivity...

Boosting support vector machines for cancer discrimination tasks.

Computers in biology and medicine
Cancer is a complex disease that is caused by rapid alteration of genes. Prediction of the state of cancer in advance contributes to a better understanding of its mechanism and improves the cancer therapy process. For example, predicting the malignan...

Identifying Phage Virion Proteins by Using Two-Step Feature Selection Methods.

Molecules (Basel, Switzerland)
Accurate identification of phage virion protein is not only a key step for understanding the function of the phage virion protein but also helpful for further understanding the lysis mechanism of the bacterial cell. Since traditional experimental met...

Transfer learning with deep convolutional neural network for liver steatosis assessment in ultrasound images.

International journal of computer assisted radiology and surgery
PURPOSE: The nonalcoholic fatty liver disease is the most common liver abnormality. Up to date, liver biopsy is the reference standard for direct liver steatosis quantification in hepatic tissue samples. In this paper we propose a neural network-base...

Establishment of a SVM classifier to predict recurrence of ovarian cancer.

Molecular medicine reports
Gene expression data using retrieved ovarian cancer (OC) samples were used to identify genes of interest and a support vector machine (SVM) classifier was subsequently established to predict the recurrence of OC. Three datasets (GSE17260, GSE44104 an...

Deep Learning-Based Enhanced Presentation Attack Detection for Iris Recognition by Combining Features from Local and Global Regions Based on NIR Camera Sensor.

Sensors (Basel, Switzerland)
Iris recognition systems have been used in high-security-level applications because of their high recognition rate and the distinctiveness of iris patterns. However, as reported by recent studies, an iris recognition system can be fooled by the use o...

Identifying individuals with attention deficit hyperactivity disorder based on temporal variability of dynamic functional connectivity.

Scientific reports
Attention deficit hyperactivity disorder (ADHD) is a common disorder that emerges in school-age children. The diagnostic model based on neuroimaging features could be beneficial for ADHD in twofold: identifying individuals with ADHD and discovering t...