Prevalence and predictors of social anxiety disorders among Malaysian secondary school students during the COVID-19 pandemic: Exploring the influence of internet gaming disorder and impulsivity.

This study aimed to investigate the prevalence of social anxiety disorder (SAD) among Malaysian secondary school students during the COVID-19 pandemic and to explore its correlations with demographic variables, impulsivity behavior, and internet gaming disorder (IGD). A total of 1574 participants from 12 government secondary schools across five Malaysian states, comprising 569 males and 1005 females, completed an online questionnaire containing validated Malay versions of the Social Interaction Anxiety Scale, Barratt Impulsiveness Scale, and Internet Gaming Disorder Scale - Short Form. The findings revealed a notable SAD prevalence rate of 40.

A variable dimensional chaotic map-based medical image encryption algorithm with multi-mode.

Since the COVID-19 pandemic, telemedicine or non-face-to-face medicine has increased significantly. In practice, various types of medical images are essential to achieve effective telemedicine. Medical image encryption algorithms play an irreplaceable role in the fast and secure transmission and storage of these medical images.

The prevalence of internet gaming disorders and the associated psychosocial risk factors among adolescents in Malaysian secondary schools.

Internet Gaming Disorder (IGD) has been placed under the conditions for further study segment in DSM-5. The purpose of the current study was to develop a preliminary psychosocial model as a reference for providing appropriate intervention, particularly for adolescents with IGD. A total of 5290 adolescents from secondary schools in seven states in Malaysia were recruited by using proportionate random sampling.

A plain-image correlative semi-selective medical image encryption algorithm using enhanced 2D-logistic map.

Modern medical examinations have produced a large number of medical images. It is a great challenge to transmit and store them quickly and securely. Existing solutions mainly use medical image encryption algorithms, but these encryption algorithms, which were developed for ordinary images, are time-consuming and must cope with insufficient security considerations when encrypting medical images.

A bibliometric of publication trends in medical image segmentation: Quantitative and qualitative analysis.

Purpose: Medical images are important in diagnosing disease and treatment planning. Computer algorithms that describe anatomical structures that highlight regions of interest and remove unnecessary information are collectively known as medical image segmentation algorithms. The quality of these algorithms will directly affect the performance of the following processing steps.

Evaluation and comparison of current fetal ultrasound image segmentation methods for biometric measurements: a grand challenge.

This paper presents the evaluation results of the methods submitted to Challenge US: Biometric Measurements from Fetal Ultrasound Images, a segmentation challenge held at the IEEE International Symposium on Biomedical Imaging 2012. The challenge was set to compare and evaluate current fetal ultrasound image segmentation methods. It consisted of automatically segmenting fetal anatomical structures to measure standard obstetric biometric parameters, from 2D fetal ultrasound images taken on fetuses at different gestational ages (21 weeks, 28 weeks, and 33 weeks) and with varying image quality to reflect data encountered in real clinical environments.

Integration of local and global features for anatomical object detection in ultrasound.

The use of classifier-based object detection has found to be a promising approach in medical anatomy detection. In ultrasound images, the detection task is very challenging due to speckle, shadows and low contrast characteristic features. Typical detection algorithms that use purely intensity-based image features with an exhaustive scan of the image (sliding window approach) tend not to perform very well and incur a very high computational cost.