18 research outputs found
A Data Analytics Suite for Exploratory Predictive, and Visual Analysis of Type 2 Diabetes
Long-term management of chronic disorders such as Type 2 Diabetes (T2D) requires personalised care for patients due to variation in patient characteristics and their response to a specific line of treatment. The availability of large volumes of electronic records of T2D patient data provides opportunities for application of big data analysis to gain insights into the disease manifestation and its impact on patients. Data science in healthcare has the potential to identify hidden knowledge from the database, re-confirm existing knowledge, and aid in personalising treatment. In this paper, we present a suite of data analytics for T2D disease management that allows clinicians and researchers to identify associations between different patient biological markers and T2D related complications. The analytics suite consists of exploratory, predictive, and visual analytics with capabilities including multi-tier classification of T2D patient profiles that associate them to specific conditions, T2D related complication risk prediction, and prediction of patient response to a particular line of treatment. The analytics presented in this paper explore advanced data analysis techniques, which are potential tools for clinicians in decision-making that can contribute to better management of T2D
Content-aware downlink scheduling for LTE wireless systems : a survey and performance comparison of key approaches
Rate-Distortion and Rate-Quality Performance Analysis of HEVC compression of Medical Ultrasound Videos
A comparative performance evaluation of the HEVC standard with its predecessor H.264/AVC for medical videos over 4G and beyond wireless networks
High-Efficiency Video Coding (HEVC) is the latest video compression standard developed by the Joint Collaborative Team on Video Coding (JCT-VC). This standard is developed with an aim to reduce the video bitrate requirements by 50% with no degradation in the video quality. In the field of telemedicine, the HEVC standard can help in lowering the bitrate requirements for coding medical videos and thus enhance their compression efficiency and transmission performance over communication channels. In this paper, a comparative performance evaluation of the HEVC standard with its predecessor the H.264/AVC has been carried out in the context of medical videos. The evaluation results are achieved using three different configuration modes currently provided by the JCT-VC team, namely the random access, low delay and intra configurations. In order to perform a fair comparative evaluation, the H.264/AVC standard is also configured to match as close as possible to the configuration modes of the HEVC standard. The encoded videos of both HEVC and H.264 standards are transmitted over simulated 4G networks in order to study its influence on system resource utilisation and transmission efficiency. The test results show that the HEVC standard gives higher compression efficiency over the H.264/AVC standard, resulting in a reduction in bitrate requirements, which further helps in achieving better quality transmission over LTE/LTE-A networks