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000930028 020__ $$a9783030368449
000930028 020__ $$a3030368440
000930028 035__ $$aSP(OCoLC)on1145562849
000930028 035__ $$aSP(OCoLC)1145562849
000930028 040__ $$aEBLCP$$beng$$epn$$cEBLCP$$dGW5XE$$dOCLCQ
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000930028 050_4 $$aTK5102.9
000930028 08204 $$a621.3822$$223
000930028 1112_ $$aIEEE Signal Processing in Medicine and Biology Symposium$$d(2018 :$$cPhiladelphia, Pa.)
000930028 24510 $$aSignal processing in medicine and biology :$$bemerging trends in research and applications /$$cIyad Obeid, Ivan Selesnick, Joseph Picone, editors.
000930028 260__ $$aCham :$$bSpringer,$$c©2020.
000930028 300__ $$a1 online resource (285 pages)
000930028 336__ $$atext$$btxt$$2rdacontent
000930028 337__ $$acomputer$$bc$$2rdamedia
000930028 338__ $$aonline resource$$bcr$$2rdacarrier
000930028 500__ $$a"This edited volume consists of the expanded versions of the exceptional papers presented at the 2018 IEEE Signal Processing in Medicine and Biology (IEEE SPMB) Symposium held at Temple University in Philadelphia, Pennsylvania, USA"--Page v.
000930028 504__ $$aIncludes bibliographical references and index.
000930028 5050_ $$aChapter 1. An Analysis of Automated Parkinsons Diagnosis Using Voice: Methodology and Future Directions -- Chapter 2. Noninvasive Vascular Blood Sound Monitoring Through Flexible Microphone -- Chapter 3. The Temple University Hospital Digital Pathology Corpus -- Chapter 4. Transient Artifacts Suppression in Time Series via Convex Analysis -- Chapter 5. The Hurst Exponent A Novel Approach for Assessing Focus During Trauma Resuscitation -- Chapter 6. Gaussian Smoothing Filter For Improved EMG Signal Modeling -- Chapter 7. Clustering of SCG Events Using Unsupervised Machine Learning -- Chapter 8. Deep Learning Approaches for Automated Seizure Detection from Scalp Electroencephalograms.
000930028 506__ $$aAccess limited to authorized users.
000930028 520__ $$aThis book covers emerging trends in signal processing research and biomedical engineering, exploring the ways in which signal processing plays a vital role in applications ranging from medical electronics to data mining of electronic medical records. Topics covered include statistical modeling of electroencephalograph data for predicting or detecting seizure, stroke, or Parkinsons; machine learning methods and their application to biomedical problems, which is often poorly understood, even within the scientific community; signal analysis; medical imaging; and machine learning, data mining, and classification. The book features tutorials and examples of successful applications that will appeal to a wide range of professionals and researchers interested in applications of signal processing, medicine, and biology. Covers traditional signal processing topics within biomedicine Promotes collaboration between healthcare practitioners and signal processing researchers Presents tutorials and examples of successful applications.
000930028 588__ $$aDescription based on print version record.
000930028 650_0 $$aSignal processing$$vCongresses.
000930028 650_0 $$aBiomedical engineering$$vCongresses.
000930028 7001_ $$aObeid, Iyad,$$d1975-
000930028 7001_ $$aSelesnick, Ivan.
000930028 7001_ $$aPicone, Joseph.
000930028 77608 $$iPrint version:$$aObeid, Iyad.$$tSignal Processing in Medicine and Biology : Emerging Trends in Research and Applications.$$dCham : Springer International Publishing AG, ©2020$$z9783030368432
000930028 852__ $$bebk
000930028 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-030-36844-9$$zOnline Access$$91397441.1
000930028 909CO $$ooai:library.usi.edu:930028$$pGLOBAL_SET
000930028 980__ $$aEBOOK
000930028 980__ $$aBIB
000930028 982__ $$aEbook
000930028 983__ $$aOnline
000930028 994__ $$a92$$bISE