Browsing by Subject "machine learning"
Now showing items 1-11 of 11
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Bayesian estimate of mean proper scores for diversity-enhanced active learning
(2023-12-15)The effectiveness of active learning largely depends on the sampling efficiency of the acquisition function. Expected Loss Reduction (ELR) focuses on a Bayesian estimate of the reduction in classification error, and more ... -
Corrigendum: Machine learning for the detection of social anxiety disorder using e ective connectivity and graph theory measures
(2023-07-24)Here’s the corrected funding and acknowledgment statements as requested: Funding This research was supported by the Ministry of Education, Malaysia under the Higher Institute Center of Excellence (HiCOE) scheme awarded ... -
Corrigendum: Machine learning for the detection of social anxiety disorder using effective connectivity and graph theory measures (Frontiers in Psychiatry, (2023), 14, (1155812), 10.3389/fpsyt.2023.1155812)
(2023)In the published article, there was an error in the Funding statement. The correct Funding and Acknowledgment statements appear below. -
Ensemble learning of myocardial displacements for myocardial infarction detection in echocardiography
(2023-10-13)Background: Early detection and localization of myocardial infarction (MI) can reduce the severity of cardiac damage through timely treatment interventions. In recent years, deep learning techniques have shown promise for ... -
Machine learning for the detection of social anxiety disorder using effective connectivity and graph theory measures
(2023)Introduction: The early diagnosis and classification of social anxiety disorder (SAD) are crucial clinical support tasks for medical practitioners in designing patient treatment programs to better supervise the progression ... -
Semi-supervised machine learning of optical in-situ monitoring data for anomaly detection in laser powder bed fusion
(2022)Laser powder bed fusion (L-PBF) is one of the most widely used metal additive manufacturing technology for fabrication of functional and structural components. However, inconsistency in quality and reliability of L-PBF ... -
Toward forecasting future day air pollutant index in Malaysia
(2020-10-14)The association of air pollution and the magnitude of adverse health effects are receiving close attention from the world. The effects of air pollution were found to be most significant for children, elderly, and patients ... -
Towards a Comprehensive Solution for a Vision-Based Digitized Neurological Examination
(2022-08-08)The ability to use digitally recorded and quantified neurological exam information is important to help healthcare systems deliver better care, in-person and via telehealth, as they compensate for a growing shortage of ... -
Towards a comprehensive solution for a vision-based digitized neurological examination
(2022-08)The ability to use digitally recorded and quantified neurological exam information is important to help healthcare systems deliver better care, in-person and via telehealth, as they compensate for a growing shortage of ... -
Use of a convolutional neural network and quantitative ultrasound for diagnosis of fatty liver
(2020-10-30)Quantitative ultrasound (QUS) was used to classify rabbits that were induced to have liver disease by placing them on a fatty diet for a defined duration and/or periodically injecting them with CCl4. The ground truth of ... -
Use of a convolutional neural network and quantitative ultrasound for diagnosis of fatty liver
(2022-03-01)Quantitative ultrasound (QUS) was used to classify rabbits that were induced to have liver disease by placing them on a fatty diet for a defined duration and/or periodically injecting them with CCl4. The ground truth of ...
