AIMC Topic: Support Vector Machine

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Prediction of venous thromboembolism with machine learning techniques in young-middle-aged inpatients.

Scientific reports
Accumulating studies appear to suggest that the risk factors for venous thromboembolism (VTE) among young-middle-aged inpatients are different from those among elderly people. Therefore, the current prediction models for VTE are not applicable to you...

COVID-19 cough classification using machine learning and global smartphone recordings.

Computers in biology and medicine
We present a machine learning based COVID-19 cough classifier which can discriminate COVID-19 positive coughs from both COVID-19 negative and healthy coughs recorded on a smartphone. This type of screening is non-contact, easy to apply, and can reduc...

Predictive analytics for step-up therapy: Supervised or semi-supervised learning?

Journal of biomedical informatics
BACKGROUND: Step-up therapy is a patient management approach that aims to balance the efficacy, costs and risks posed by different lines of medications. While the initiation of first line medications is a straightforward decision, stepping-up a patie...

Multispectral co-occurrence of wavelet coefficients for malignancy assessment of brain tumors.

PloS one
Brain tumor is not most common, but truculent type of cancer. Therefore, correct prediction of its aggressiveness nature at an early stage would influence the treatment strategy. Although several diagnostic methods based on different modalities exist...

Robust cost-sensitive kernel method with Blinex loss and its applications in credit risk evaluation.

Neural networks : the official journal of the International Neural Network Society
Credit risk evaluation is a crucial yet challenging problem in financial analysis. It can not only help institutions reduce risk and ensure profitability, but also improve consumers' fair practices. The data-driven algorithms such as artificial intel...

Eye-Movement-Controlled Wheelchair Based on Flexible Hydrogel Biosensor and WT-SVM.

Biosensors
To assist patients with restricted mobility to control wheelchair freely, this paper presents an eye-movement-controlled wheelchair prototype based on a flexible hydrogel biosensor and Wavelet Transform-Support Vector Machine (WT-SVM) algorithm. Cons...

Machine learning approach in mortality rate prediction for hemodialysis patients.

Computer methods in biomechanics and biomedical engineering
Kernel support vector machine algorithm and -means clustering algorithm are used to determine the expected mortality rate for hemodialysis patients. The national nephrology database of Montenegro has been used to conduct this research. Mortality rate...

Experimental and numerical diagnosis of fatigue foot using convolutional neural network.

Computer methods in biomechanics and biomedical engineering
Fatigue is an essential criterion for physiotherapy in injured athletes. Muscle fatigue mechanism also is a crucial matter in designing a workout program. It is mainly related to physical injury, cerebrovascular accident, spinal cord injury, and rheu...

Machine learning for surgical time prediction.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Operating Rooms (ORs) are among the most expensive services in hospitals. A challenge to optimize the OR efficiency is to improve the surgery scheduling task, which requires the estimation of surgical time duration. Surgeons...

Development and validation of consensus machine learning-based models for the prediction of novel small molecules as potential anti-tubercular agents.

Molecular diversity
Tuberculosis (TB) is an infectious disease and the leading cause of death globally. The rapidly emerging cases of drug resistance among pathogenic mycobacteria have been a global threat urging the need of new drug discovery and development. However, ...