商品描述
Signal Processing in Medicine and Biology: Applications of Deep Learning to the Health Sciences presents expanded versions of selected papers from the 2023 IEEE Signal Processing in Medicine and Biology Symposium (IEEE SPMB) at Temple University. The symposium presents multidisciplinary research across a wide range of topics in the life sciences. The Neural Engineering Data Consortium hosts the symposium to promote machine learning and big data applications in bioengineering. Topics covered include: - Signal and image analysis (e.g., EEG, ECG, MRI); - Machine learning, data mining, and classification; - Big data resources and applications; - Applications of quantum computing; - Digital pathology; - Computational biology; - Genomics, genetics, proteomics. Applications of particular interest at the 2023 symposium included digital pathology, computational biology, genomics, genetics, and proteomics. The book features tutorials and examples of successful applications that will appeal to many professionals and researchers in signal processing, medicine, and biology. For students and professionals new to the field, the book offers an easy-to-understand introduction to various bioengineering topics. For professionals active in the field, it provides essential algorithmic details on valuable benchmarks for the technology.
商品描述(中文翻譯)
《醫學與生物學中的信號處理：深度學習在健康科學中的應用》呈現了2023年在天普大學舉行的IEEE醫學與生物學信號處理研討會（IEEE SPMB）中選定論文的擴展版本。該研討會展示了生命科學領域內多學科的研究，神經工程數據聯盟主辦此研討會，以促進機器學習和大數據在生物工程中的應用。
涵蓋的主題包括：
- 信號和影像分析（例如，EEG、ECG、MRI）；
- 機器學習、數據挖掘和分類；
- 大數據資源和應用；
- 量子計算的應用；
- 數位病理學；
- 計算生物學；
- 基因組學、遺傳學、蛋白質組學。
2023年研討會中特別感興趣的應用包括數位病理學、計算生物學、基因組學、遺傳學和蛋白質組學。這本書包含了成功應用的教程和範例，將吸引許多信號處理、醫學和生物學領域的專業人士和研究人員。對於新進入該領域的學生和專業人士，這本書提供了易於理解的各種生物工程主題的介紹。對於活躍於該領域的專業人士，則提供了有關技術的重要基準的基本算法細節。
作者簡介
Ammar Ahmed, Ph.D., is a Radar Signal Processing Engineer at Aptiv in Agoura Hills, CA, USA, where he contributes to the development of advanced mobility solutions, focusing on innovations in autonomous driving and safety systems. He earned his Ph.D. from Temple University, USA, in 2021. From 2011 to 2016, Dr. Ahmed worked as an electrical engineer for the National Tokamak Fusion Program in Pakistan, where he was responsible for developing embedded system design for spherical tokamaks. His research interests include signal processing, data analysis, optimization, and radar systems. Joseph Picone, Ph.D., is a Professor of Electrical and Computer Engineering at Temple University, where he directs the Institute for Signal and Information Processing (ISIP) and the Neural Engineering Data Consortium (NEDC). His primary expertise is in machine learning for applications in the health sciences. A common theme throughout his research career has been the development of big data resources that enable research on advanced statistical modeling paradigms. The data and resources developed by NEDC are used by over ten thousand researchers worldwide. The ISIP web site is one of the oldest web sites devoted to the development of open source resources. Dr. Picone has been an active researcher in various aspects of speech processing for over 40 years. His research has been funded by government agencies such as The National Science Foundation, The National Institutes of Health and DoD, as well as many industrial partners (Texas Instruments, Natus). He has published over 300 technical papers and holds eight patents.
作者簡介(中文翻譯)
Ammar Ahmed, Ph.D., 是美國加州阿古拉山的Aptiv公司的雷達信號處理工程師，專注於自動駕駛和安全系統的創新，為先進的移動解決方案的開發做出貢獻。他於2021年在美國天普大學獲得博士學位。從2011年到2016年，Ahmed博士在巴基斯坦的國家托卡馬克聚變計劃擔任電氣工程師，負責為球形托卡馬克開發嵌入式系統設計。他的研究興趣包括信號處理、數據分析、優化和雷達系統。 Joseph Picone, Ph.D., 是天普大學電氣與計算機工程系的教授，負責信號與信息處理研究所（ISIP）和神經工程數據聯盟（NEDC）。他的主要專長是應用於健康科學的機器學習。在他的研究生涯中，一個共同主題是開發大數據資源，以促進對先進統計建模範式的研究。NEDC開發的數據和資源被全球超過一萬名研究人員使用。ISIP網站是最早致力於開發開源資源的網站之一。Picone博士在語音處理的各個方面活躍研究超過40年。他的研究得到了國家科學基金會、國家衛生研究院和國防部等政府機構以及許多工業夥伴（德州儀器、Natus）的資助。他已發表超過300篇技術論文並擁有八項專利。
