Explainable Large Language Models in Healthcare Applications

Name: Explainable Large Language Models in Healthcare Applications
Brand: Springer
SKU: 9783032150875
Price: 19030.0 INR
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by Azadeh Zamanifar , Amir Taherkordi , Amirfarhad Farhadi

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ISBN13: 9783032150875
Binding: Hardcover
Subject: N/A
Publisher: Springer
Publisher Imprint: Springer
Publication Date: May 20, 2026
Pages: 325
Original Price: GBP 149.99
Language: English
Edition: N/A
Item Weight: 658 grams
BISAC Subject(s): Artificial Intelligence / General

About The Author

Azadeh Zamanifar is currently head of AI/ software department and an assistant professor of Islamic Azad university, science and research branch. Her research interests include IoT based health care systems, machine learning, deep learning, and distributed systems. She received B.SC in Tehran university in 2002. She received her M.SC from Iran university of science and technology in 2008. She received her Ph.D. from Shahid Beheshti university in December 2016.

AMIR TAHERKORDI (Member, IEEE) is a Full Professor at the Department of Informatics, University of Oslo (UiO). He received his Ph.D. degree from the Informatics Department, UiO in 2011. After completing his Ph.D. studies, Amir joined Sonitor Technologies as a Senior Embedded Software Engineer. From 2013 to 2018, he was a researcher in the Networks and Distributed Systems (ND) group at the Department of Informatics, UiO. He has so far published several articles in high-ranked conferences and journals, and he has experience from several national (Norwegian Research Council) and international (European research funding agencies) research projects. He is an Associate Editor of IEEE Transactions on Mobile Computing and IEEE Transactions on Network Science and Engineering. Amir's research interests are broadly on resource-efficiency, scalability, adaptability, dependability, mobility and data-intensiveness of distributed systems designed for emerging computing technologies, such as Internet of Things (IoT), Fog/Edge/Cloud Computing, and Cyber-Physical Systems (CPS).

Amirfarhad Farhadi holds a Ph.D. in Artificial Intelligence and is currently a Postdoctoral Fellow at Iran University of Science and Technology. He also serves as an Adjunct Professor in the Department of Computer Engineering at the Science and Research Branch of Islamic Azad University. His research expertise spans Artificial Intelligence (AI), machine learning, deep learning, transfer learning, reinforcement learning, natural language processing (NLP), and healthcare systems. Dr. Farhadi serves as a reviewer for esteemed journals, including IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) and IEEE Transactions on Neural Networks and Learning Systems, among others. In addition to his academic contributions, he holds patents in robotics and actively participates in the AI industry, focusing on innovative applications and technological advancements.

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