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Get primed on Artificial Intelligence in healthcare at HIMSS 17

February 16, 2017 By HealthIsCool 1 Comment

AI

Artificial Intelligence Networking Meetup at HIMSS 17

On Monday, February 20th, Nardo Manaloto and Wen Dombrowski MD MBA of CATALAIZE are hosting an Artificial Intelligence (AI) Networking Meetup at HIMSS 17. Health IT colleagues are invited to join them between 3 pm and 4:30 pm in room 414D on the 4th floor of the West Convention Hall building at the conference in Orlando.

According to CATALAIZE CEO Nardo Manaloto, “We want to create a community of people interested in how Artificial Intelligence can be applied to improve all aspects of health – from patient experience, to clinical care, and business automation.”

Dr. Dombrowski hopes participants will learn from each other and find ways to collaborate, “Even if you are not an algorithm engineer, AI is becoming more ubiquitous in our lives and is impacting everyone. Within healthcare, it is exciting to learn about the new ways that AI can improve care.” For example:

  • Machine Learning for risk prediction & intervention
  • Deep Learning for drug discovery
  • Computer Vision for radiology image interpretation
  • Chatbots for customer service
  • Intelligent Virtual Agents as care managers
  • Robots for hospital automation
  • Speech Recognition & Natural Language Processing to support caregivers

Demystifying Big Data and Machine Learning in HealthcarePrashant Natarajan, author of the book, “Demystifying Big Data and Machine Learning in Healthcare”, will also be part of the meetup and five copies of his book will be given away to attendees.

What is the most important topic for healthcare to address regarding AI?

Dr. Wen Dombrowski: The promise of AI is that it will automate tasks and uncover new insights faster to improve patient experience, decrease costs and business inefficiencies.

However, since healthcare deals with human lives, safeguards and validation testing are needed to ensure the appropriateness of AI interpretations and recommendations, especially since medical context is complex, biases in training data are prevalent, and the impact on patients could be significant.

What are the most interesting startups in healthcare based on AI at the moment, and why?

Nardo Manaloto: Atomwise is an interesting startup because it uses Deep Learning Neural Networks to discover new drug molecules at a pace we’ve never seen before. There are many other healthcare AI companies, including this list of 106 startups by CB Insights.

AI_healthcare_map

What is the problem you would like to see a startup address with AI?

Nardo Manaloto: I would like startups to address AI data infrastructure needs such as knowledge context and ensuring all AI calculations and interactions are correct and appropriate.

Dr. Wen Dombrowski: I am also interested in AI that identifies needs and automatically matches them to appropriate resources.

Healthcare is relatively slow to adapt to change, and technological change in AI is exponential. How can healthcare handle this conundrum?

Dr. Wen Dombrowski: Healthcare has been one of the slowest industries to adopt technology, even with the recent emphasis on EHR software. Awareness of emerging and existing technologies beyond EHRs is important for culture change. We’ve been educating healthcare executives about this and as consumer electronics like Amazon Alexa become more widely available, healthcare leaders and consumers will become less intimidated by technology and start thinking creatively about how it can be useful in healthcare and their daily lives.

Nardo Manaloto: One compelling aspect of AI is that it can be self-learning and can document evidence to support outcome changes and improvements. AI can also leapfrog current solutions with next generation solutions created by AI itself. This provides an environment for rapid iteration and adoption.

How can patients benefit from AI in healthcare? Will AI promote more or less patient engagement as machines become more involved?

Dr. Wen Dombrowski: Patients will benefit from AI health recommendations and life guidance precisely tailored to their personal situation. This will create right-sized patient engagement based on personal needs and empowered by relevant encouragement and information for self-care. Patients will also have better access to care by interacting with AI Assistants that will save them time, money, and frustration.

There are also a number of other AI and Machine Learning events taking place at HIMSS 17.

AI HIMSS17

Manaloto says a #HIMSS17 session that sounds interesting is “Emerging Impacts of Artificial Intelligence on Healthcare IT” , “This session is interesting because it aligns with the goal of our AI Meetup and focuses on high value use cases with financial return of investment. This will catalyze more development and adoption of AI in healthcare organizations interested in meeting value-based payment requirements and population health.”

“As the field of AI begins to mature, we also hope this group of healthcare thought leaders will champion best practices and standards that enable rapid, safe, and useful AI solutions.” – Wen Dombrowski MD MBA

AI, Deep Learning, and Machine Learning: A Primer from Andreessen Horowitz

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HealthIsCool

@HealthIsCool / Angela Dunn writes about the future of health covering tech giants, startups and innovation. Topics of interest include: artificial intelligence (AI), blockchain, precision medicine, and other trends. Follow on Twitter at @HealthIsCool.
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Filed Under: 3, Health care, healthcare innovation, Healthcare IT, Internet of Things, Radiology IT Tagged With: AI, Amazon Alexa, artificial intelligence, automation, CATALAIZE, chatbots, deep learning, healthcare emerging technology, HIMSS17, machine learning, Nardo Manaloto, Patient Engagement, patient experience, virtual assistants, Web Dombrowski MD

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