Welcome to the Better Communication Results podcast vidcast, edition number 120.
In today’s show:
- Is Radiology ripe for AI amalgamation?
- Talking about the fusion of AI and cybersecurity
- How some AI platforms are using natural language processing
Radiology is ripe for an AI amalgamation
“Artificial intelligence will not replace radiologists … but radiologists who use AI will replace radiologists who don’t.”
Curtis Langlotz, MD, PhD
Dr Langlotz is a Stanford Professor and Director, and he thinks the future of radiology and radiologists is rosy. But only if practitioners embrace the new tech.
Medical imaging’s present and future is human plus machine, says Mary Tierney. Radiologists are intrigued with AI’s potential to expedite and improve their ability to interpret images. Some are starting to benefit from AI apps, and test plenty more of their own and commercial apps in development. Like many other industries, healthcare looks to AI to quickly wring insights from data, making information more useful and actionable. Machines can’t think, but they can learn. Radiology is learning how they will mold the future.
“If you generate more useful data, you become a better consultant,” says Gary Wendt, MD, MBA, enterprise director of medical imaging and vice chair of informatics at the University of Wisconsin School of Medicine and Public Health in Madison. “If you’re actually giving more people more actionable data, you as a physician are a more valuable part of the care process.”
Beyond individual AI apps, the differentiator for both imaging and healthcare is going to be looking at large, longitudinal datasets, offers Geisinger’s Fornwalt. “Where you take a little cross-section of data and look forward and predict from that. That’s what machines are good at. We can’t do that as physicians…So we’re going to leverage that predictive power to make a difference.”
The advantage AI brings is a deeper look into the data, and “a recognition that there are opportunities to do more with what we’re acquiring and what can we unlock.” Machine intelligence sees more, differently, which “simply is just not possible no matter how much time a human sits looking at it.”
Talking about the fusion of AI and cybersecurity
There’s little discussion out in the open, but a lot of activity behind the scenes regarding the meshing of AI and cybersecurity.
This is of particular interest to Lee Hopkins here at Better Communication
True black-hat hackers don’t need to read a book such as that — they are using AI to test their own malicious code before they unleash it on attacks. Which is where AI is coming into the mix for organisations.
Organisations are now having to add machine learning into clean and dirty traffic datasets in order to prepare themselves for the inevitable attacks on their systems.
As CIOapplications.com says, prepare to use all means at your disposal to beat the hackers. In the short term, investigate how AI, ML and blockchain technologies can ensure advanced security.
says, prepare to use all means at your disposal to beat the hackers. In the short term, investigate how AI, ML and blockchain technologies can ensure advanced security.
And finally, how some AI platforms are using natural language processing
Natural Language Processing, or NLP, is rife on the internet and on your smartphone. Think Alexa, think Siri, think Cortana, think Google’s Assistant. Think Amazon, think Google Search and Google Analytics, think Facebook. Chances are, wherever you go, AI will be there in some shape or form.
What’s driving a lot of consumer-facing AI at the moment is voice-activated applications. Not just your smartphone or smartspeaker, but chatbots. Chatbots are a huge and growing part of the NLP scene.
The NLP scene is also growing. To give you some idea, voice-activated applications are expected to be worth US$13.4 billion by next year.
Tim Keary over at InformationAge.com says NLP is key to understanding sentiment analysis. With the volume of data available to analysts now, using AI technology is the only way to be able to efficiently drill down and uncover core views and sentiment.
And Tim is bullish on chatbots, too. “Chatbots function well within the finance industry because they allow organisations to automate routine customer service activity. Rather than paying a representative to answer questions live, a bank can invest in a chatbot to manage lower priority support tasks.”
With more applications processing more and more data, the machines are only going to get smarter and more able to meet our needs. The future is bright for NLP.
And that’s it for another episode of the Better Communication Results vidcast. Subscribe to our vidcast over at YouTube, or subscribe to our blog by filling in the form below.
Until next time, take care, take some communication risks, because you never know what is going to pay off, and communicate with passion.
Previous editions of the Better Communication Results vidcast: