Radiology, Artificial Intelligence and HealthTech discussion with Dr. Rizwan Malik and João Bocas

João Bocas - The #Wearables Expert ™ interviews Dr. Rizwan Malik, Radiologist, HealthTech / AI Innovation and Strategy Consultant. In this episode, we talked about #Radiology #AI and #HealthTech We checked the pulse of Digital Healthcare as the industry transforms in a fast manner. Here are the questions we've addressed: 01:14 What's happening in the Radiology Innovation world right now? 04:12 What's the real value of AI in Healthcare? 08:49 What is considered red tape that may work against industry innovation and slows down adoption? Connect with Dr. Rizwan Malik : LinkedIn: https://www.linkedin.com/in/rizwan-malik-93173778/ Twitter: https://twitter.com/rijan44 Share this episode with your networks: https://youtu.be/QumisFKXPnY Feel free to 📣 CONNECT WITH ME 🟢: LinkedIn: https://www.linkedin.com/in/joaobocas/ Twitter: https://twitter.com/WearablesExpert Please check our Digital Health Platform - CliniTouch Vie https://bit.ly/CliniTouch_Vie Industry Partner: Isaac Care https://bit.ly/isaac-care The healthcare industry is undergoing a major transformation, and radiologists are at the forefront of this change. Radiology is an important part of the healthcare system that has traditionally been highly manual and time-consuming. The process of reading images and interpreting them can be time consuming, but it's also highly important, as it helps doctors make diagnoses and come up with treatment plans. AI has been applied to various aspects of healthcare, including radiology. By using AI to analyze radiological images, radiologists are able to spend less time on routine tasks and more on complex cases that need their attention. In recent years, artificial intelligence has become a hot-button topic in the healthcare industry. The potential benefits of AI in radiology are vast--it can help doctors make faster diagnoses and improve accuracy, which can ultimately save lives. But the technology still has a long way to go before it can be implemented on a large scale. The main challenge with implementing AI in radiology is that radiologists need to be able to trust the results they get from an algorithm or machine learning system. They don't want their careers to be taken over by an algorithm that makes mistakes all the time or doesn't take into account all of the factors they consider when making a diagnosis. In order for AI-based systems to gain widespread adoption in medicine, they need to be able to produce results that are as good as or better than those of human doctors. That means being able to detect subtle differences between different types of tumors, for example, or knowing exactly how many grams of calcium are present in bone marrow samples taken from patients with osteoporosis. Radiology is one of the oldest and most important branches of medicine. It deals with medical imaging and has a heavy focus on computer science. Radiologists are often at the forefront of new technology and use AI and other advanced methods to diagnose diseases and assess injury. The healthcare industry is always looking for ways to improve patient outcomes, reduce costs, and improve efficiency. Radiology is no different. The use of artificial intelligence in radiology has grown rapidly over the last decade as more hospitals and clinics adopt it as part of their daily operations. If you have not subscribed, do it now - https://bit.ly/3iQ6EXP