相關主題
商品描述
Implementation of artificial intelligence (AI) in radiology is an important topic of discussion. Advances in AI--which encompass machine learning, artificial neural networks, and deep learning--are increasingly being applied to diagnostic imaging. While some posit radiologists are irreplaceable, certain AI proponents have proposed to "stop training radiologists now." By compiling perspectives from experts from various backgrounds, this book explores the current state of AI efforts in radiology along with the clinical, financial, technological, and societal perspectives on the role and expected impact of AI in radiology.
商品描述(中文翻譯)
人工智慧（AI）在放射學中的應用是一個重要的討論主題。AI的進步——包括機器學習、人工神經網絡和深度學習——正日益被應用於診斷影像。雖然有些人認為放射科醫生是不可替代的，但某些AI支持者則提出「現在就停止培訓放射科醫生」。本書匯集了來自不同背景專家的觀點，探討了放射學中AI努力的現狀，以及對AI在放射學中角色和預期影響的臨床、財務、技術和社會觀點。
作者簡介
Adam E. M. Eltorai, MD, PhD
Dr Eltorai completed his graduate studies in Biomedical Engineering and Biotechnology along with his medical degree from Brown University, followed by Radiology residency at Brigham and Women's Hospital/Harvard Medical School. He is interested in the development and clinical implementation of AI applications. Dr. Eltorai has published over 130 scientific journal articles and over 25 books.
Ian Pan, MD
Dr Pan is currently a diagnostic radiology resident and former chief resident in the Brigham and Women's Hospital/Harvard Medical School Diagnostic Radiology Residency Program. He graduated from the Program in Liberal Medical Education at Brown University where he received concurrent bachelor's and master's degrees in applied mathematics-Biology and Biostatistics in 2016, as well as his MD from the Warren Alpert Medical School in 2020. His expertise lies at the intersection of artificial intelligence and medical imaging, having won multiple international competitions sponsored by organizations such as the Radiological Society of North America and published over 30 peer-reviewed manuscripts in this domain.
H. Henry Guo, MD, PhD
Dr Guo is a clinical professor in the Department of Radiology at the Stanford University School of Medicine. He received his MD and PhD in the department of Pathology at the University of Washington, followed by Radiology residency and fellowships in Nuclear Medicine and Thoracic Imaging at Stanford. Since joining the Stanford faculty in 2012, Dr. Guo focuses on cancer and lung diseases in his clinical practice and research, co-authoring over 70 research articles, book chapters, and web-based educational resources, and is a recognized expert in interpretation of thoracic CTs and PET-CTs. Dr. Guo is translating the use of quantitative CT and AI-enabled tools to clinical practice and collaborates with other faculty members as a part of the Center for Artificial Intelligence in Medicine & Imaging (AIMI) at Stanford on applications of AI to topics including interstitial lung diseases, early cancer detection, and pulmonary hypertension.
作者簡介(中文翻譯)
亞當·E·M·埃爾托萊醫生，MD，PhD
埃爾托萊醫生在布朗大學完成了生物醫學工程和生物技術的研究生學習，並獲得醫學學位，隨後在布里根婦女醫院/哈佛醫學院完成放射科住院醫師訓練。他對人工智慧應用的開發和臨床實施感興趣。埃爾托萊醫生已發表超過130篇科學期刊文章和25本書籍。
伊恩·潘醫生，MD
潘醫生目前是布里根婦女醫院/哈佛醫學院診斷放射科住院醫師，並曾擔任首席住院醫師。他畢業於布朗大學的自由醫學教育計畫，於2016年獲得應用數學-生物學和生物統計學的雙學士及碩士學位，並於2020年獲得沃倫·阿爾珀特醫學院的醫學博士學位。他的專業領域位於人工智慧與醫學影像的交集，曾贏得多項由北美放射學會等組織贊助的國際競賽，並在該領域發表超過30篇經過同行評審的手稿。
H·亨利·郭醫生，MD，PhD
郭醫生是史丹佛大學醫學院放射科的臨床教授。他在華盛頓大學的病理學系獲得醫學博士和博士學位，隨後在史丹佛完成放射科住院醫師訓練及核醫學和胸部影像的研究員訓練。自2012年加入史丹佛教職以來，郭醫生在臨床實踐和研究中專注於癌症和肺部疾病，合著超過70篇研究文章、書籍章節和網路教育資源，並在胸部CT和PET-CT的解讀方面被認可為專家。郭醫生正在將定量CT和人工智慧輔助工具應用於臨床實踐，並與其他教職員合作，作為史丹佛醫學與影像人工智慧中心（AIMI）的一部分，研究人工智慧在間質性肺病、早期癌症檢測和肺動脈高壓等主題的應用。
