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Artificial intelligence in healthcare has the potential to improve patient outcomes, but delivering AI-enabled products responsibly is essential.
This means discussing ethical and regulatory considerations regarding data privacy. He is joined by Jody Long, Director of Clinical Solutions at PointClickCare. He will address this topic in a discussion on Principles of Responsible AI at the HIMSS24 World Congress.
“What ultimately led me to this topic was my passion for helping clinicians better understand AI, to not be afraid of it, and to have confidence in using the tools,” said Long. states. “AI is not meant to replace healthcare workers at the bedside. AI is here to help healthcare professionals make better, more informed decisions. Enhance human connections by gaining access to improved clinical decision-making.”
This debate will come at an important moment for AI. Although they have shown promise in processing large amounts of data and providing clinical decisions and insights, their applications are so heterogeneous and widespread that we want to remain at the forefront of technological advances. This can be a complex situation for healthcare leaders. While applying technology in an ethical manner.
Many healthcare leaders are enthusiastic about implementing AI because of its perceived benefits. According to Medical Economy, one of the most important of these benefits is increased speed and accuracy of diagnosis, which makes it easier for healthcare providers to diagnose and treat diseases. For example, using AI he can analyze X-rays, MRI scans, and other medical images to identify patterns and abnormalities that humans might miss.
AI algorithms can also provide real-time data and recommendations that help healthcare providers quickly respond to potential emergencies, and can also aid in the management of chronic diseases. The technology also has a potential role in improving access to healthcare, such as telemedicine, where AI-enhanced telemedicine can provide remote consultations and diagnoses, eliminating the need for patient travel.
However, health economics pointed out that there may be potential risks, especially regarding security and privacy. One of the biggest risks is the potential for data breaches, as large amounts of patient data are often targeted by cybercriminals. Other types of proprietary AI attacks include data input poisoning, where a malicious attacker injects malformed data into the training set to affect the model's output, and data input poisoning, where an attacker uses an algorithm to create an alternative model. such as model extraction, which has the potential to extract sufficient information about the
The healthcare AI market, valued at $11 billion in 2021, is projected to reach $187 billion by 2030, according to Statista. Better machine learning algorithms, access to more data, cheaper hardware, and 5G connection speeds are all contributing to the rise in medical applications. AI in healthcare
“As clinicians and end users of many technology platforms, healthcare providers need to be educated on the principles of responsible AI and how their technology partners are investing in the production of these new and innovative tools. It’s important,” Long said. Hearing how we have approached AI thoughtfully and intentionally is a great starting point for anyone who wants to understand the foundations and impact of our learning in this field. ”
Her session, “Responsible AI to Improve Patient Outcomes,” will be held from 10:30 a.m. to 11:30 a.m. on March 12 in room W208C at HIMSS24 in Orlando. Check the details and register.
Jeff Lagasse I am the editor of Healthcare Finance News.
Email: jlagasse@himss.org
Healthcare Finance News is a publication of HIMSS Media.
