Engineering and clinical use of artificial intelligence (AI) with machine learning and data science advancements: radiology leading the way for future.

Over the years, many clinical and engineering methods have been adapted for testing and screening for the presence of diseases. The most commonly used methods for diagnosis and analysis are computed tomography (CT) and X-ray imaging. Manual interpretation of these images is the current gold standard but can be subject to human error, is tedious, and is time-consuming. To improve efficiency and productivity, incorporating machine learning (ML) and deep learning (DL) algorithms could expedite the process. This article aims to review the role of artificial intelligence (AI) and its contribution to data science as well as various learning algorithms in radiology. We will analyze and explore the potential applications in image interpretation and radiological advances for AI. Furthermore, we will discuss the usage, methodology implemented, future of these concepts in radiology, and their limitations and challenges.

Therapeutic advances in urology. 2021 Sep 20*** epublish ***

B M Zeeshan Hameed, Gayathri Prerepa, Vathsala Patil, Pranav Shekhar, Syed Zahid Raza, Hadis Karimi, Rahul Paul, Nithesh Naik, Sachin Modi, Ganesh Vigneswaran, Bhavan Prasad Rai, Piotr Chłosta, Bhaskar K Somani

Department of Urology, Father Muller Medical College, Mangalore, Karnataka, India., Department of Electronics and Communication, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India., Department of Oral Medicine and Radiology, Manipal College of Dental Sciences, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka 576104, India., Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India., Department of Urology, Dr. B.R. Ambedkar Medical College, Bengaluru, Karnataka, India., Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India., Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA., International Training and Research in Uro-oncology and Endourology (iTRUE) Group, Manipal, India., Department of Interventional Radiology, University Hospital Southampton NHS Foundation Trust, Southampton, UK., International Training and Research in Uro-oncology and Endourology (iTRUE) Group Manipal, India., Department of Urology, Jagiellonian University in Kraków, Kraków, Poland.