LEADER 03465nam 2200469 450 001 9910484365803321 005 20210330192103.0 010 $a3-030-60265-6 024 7 $a10.1007/978-3-030-60265-9 035 $a(CKB)4100000011743120 035 $a(DE-He213)978-3-030-60265-9 035 $a(MiAaPQ)EBC6465109 035 $a(PPN)253255104 035 $a(EXLCZ)994100000011743120 100 $a20210330d2021 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aDeep learning and edge computing solutions for high performance computing /$fA. Suresh, Sara Paiva, editors 205 $a1st ed. 2021. 210 1$aCham, Switzerland :$cSpringer,$d[2021] 210 4$dİ2021 215 $a1 online resource (XII, 279 p. 117 illus.) 225 1 $aEAI/Springer innovations in communication and computing 311 $a3-030-60264-8 327 $aIntroduction -- Deep learning methods for applications -- High performance Computing systems for applications in Healthcare -- Hyperspectral data analysis and intelligent systems -- Microarray data analysis -- Sequence analysis -- Genomics based analytics -- Disease network analysis -- Techniques for big data Analytics and health information technology -- Deep Learning and Cross-Media Methods for Big Data Representation -- Mobile edge computing for Large-scale multimodal data acquisition techniques -- Personal Big data driven approaches to collect and analyze large volumes of information from emerging technologies -- Mobile edge computing techniques for healthcare applications -- Swarm intelligence big data computing for healthcare applications -- Conclusion. 330 $aThis book provides an insight into ways of inculcating the need for applying mobile edge data analytics in bioinformatics and medicine. The book is a comprehensive reference that provides an overview of the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to the healthcare field. Topics include deep learning methods for applications in object detection and identification, object tracking, human action recognition, and cross-modal and multimodal data analysis. High performance computing systems for applications in healthcare are also discussed. The contributors also include information on microarray data analysis, sequence analysis, genomics based analytics, disease network analysis, and techniques for big data Analytics and health information technology. Identifies deep learning techniques in mobile edge data analytics and computing environments suitable for applications in healthcare; Introduces big data analytics to the sources available and possible challenges and techniques associated with bioinformatics and the healthcare domain; Features advancements in the computing field to effectively handle and make inferences from voluminous and heterogeneous healthcare data. 410 0$aEAI/Springer innovations in communication and computing. 606 $aMedical informatics 615 0$aMedical informatics. 676 $a610.285 702 $aSuresh$b A. 702 $aPaiva$b Sara$f1979- 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484365803321 996 $aDeep learning and edge computing solutions for high performance computing$92853903 997 $aUNINA