AI in Diagnostic Radiology. Este artículo no está disponible.AI in Diagnostic Radiology

AI rapidly transforms diagnostic radiology, offering powerful tools to enhance image interpretation, streamline workflows, and improve diagnostic accuracy. By utilizing deep learning algorithms trained on medical images, AI systems can detect abnormalities with precision comparable to experienced radiologists in certain contexts. These advancements have found real-world application in areas like chest X-ray analysis, mammography, CT and MRI interpretation, and triage in emergency imaging. Case-based insights demonstrate how AI assists in early disease detection, supports differential diagnosis, and reduces diagnostic errors, contributing to better patient outcomes. However, effective clinical integration requires careful validation, consideration of ethical implications, and collaboration between radiologists and AI developers to ensure technology works with, rather than replaces, human expertise. AI in Diagnostic Radiology: Clinical Applications and Case-Based Insights explores the use of AI in diagnostic radiology to enhance image analysis, improve diagnostic accuracy, and streamline clinical workflows. It explains real-world applications through case-based insights, demonstrating how AI supports radiologists in detecting and interpreting medical conditions. This book covers topics such as medical detection, deep learning, and radiology, and is a useful resource for medical professionals, computer engineers, academicians, researchers, and scientists.

Praveen Kumar is an accomplished researcher in the field of biomedical engineering and nanotechnology, with a strong focus on the intersection of artificial intelligence (AI) and medical engineering. He earned his Ph.D. in Nano-Biotechnology from the prestigious Indian Institute of Technology (IIT) Mandi, where he pioneered innovative solutions for biomedical applications, including the synthesis of advanced 2D nanomaterials and the development of nanomaterial-based antimicrobial fabrics. His work on photothermal disinfection and oil spill separation aerogels has gained widespread recognition in the scientific community. Dr. Kumar’s research has a particular emphasis on the integration of AI and nanotechnology for medical applications, with several projects focusing on smart healthcare solutions, such as microfluidics devices, point-of-care diagnostics, and wearable biosensors. His extensive research on AI’s role in medical engineering, including cancer detection and remote health monitoring, highlights his dedication to advancing healthcare technology through interdisciplinary approaches. With multiple Scopus-indexed publications and international conference presentations, Dr. Kumar has made significant contributions to biomedical imaging, nanorobotics, and AI-driven medical solutions. His recent works explore the future of AI in disease detection and management, making him a leading voice in next-generation biomedical imaging technologies. He has also mentored several research students and played a pivotal role in the design and development of healthcare devices. In recognition of his innovative research, Dr. Kumar has been awarded the prestigious SRISTI-Gandhian Young Technological Innovation Appreciation Award (GYTI) and several best paper awards at international conferences. His collaborative projects and academic contributions make him a suitable author for a book on the transformative impact of AI in medical engineering.

Prateek Verma was born on 14 th September 1988. He completed his B.Tech in Electronics and Communication Engineering, M.Tech and Ph.D. in Geomatics Engineering from IIT Roorkee along with Post Doc from IIT Bombay. He is currently working as an Assistant Professor in Department of Artificial Intelligence and Machine Learning at Faculty of Engineering and Technology, Datta Meghe Institute of Higher Education and Research (DU) at Wardha Maharashtra India. He received DAAD TU9 Masters Sandwiched Scholarship to pursue M.Tech Research in Germany in 2012. His research areas include Machine Learning, Geospatial Technology, GIS, Healthcare and Natural Resource Management. He currently has more than 20 papers in International Journals/Conferences including more than 5 papers in SCI/SCIE Journals.

Gaurav Vedprakash Mishra is currently working as Professor in the Department of Radiodiagnosis, Jawaharlal Nehru Medical College and Pro Vice Chancellor, Datta Meghe Institute of Higher Education and Research (deemed to be university). He has more than 100 publications indexed in Scopus, more than 65 publications indexed in Web of Science and 48 publications indexed in PubMed which are spread across multiple scientific areas such as radiology, health professions education, research methodology, artificial intelligence and medicine.

Gopal Singh Phartiyal is currently working as Research Fellow in Machine Learning at the School of Earth and Environment, University of Leeds, Leeds, United Kingdom. He is a PhD in ‘Deep Learning for Earth Observation Data’ from Indian Institute of Technology Roorkee, Roorkee, India. He has more than 10 years of experience in developing earth observation data applications including projects for GAIL, RailTel, DST, and INRIA(France). He has received fellowships from MHRD and IFCAM-CEFIPRA for his research work.

Anurag A. Luharia is presently serving as the Head & Consultant Medical Physicist & Radiological Safety Officer-III (Radiotherapy / Radiology / Nuclear Medicine) at Datta Meghe Institute of Higher Education and Research, Sawangi (Meghe), Wardha. He has more than 90 scientific publications in various indices. He is the author of 14 books and contributed to more than 30 chapters in multiple books. He has more than 18 years of clinical experience. He has commissioned and established various medical diagnostic, and therapeutic Radiation facilities.