{"id":2349,"date":"2024-12-14T01:40:35","date_gmt":"2024-12-14T01:40:35","guid":{"rendered":"https:\/\/happy-liskov.74-208-176-141.plesk.page\/2024\/?p=2349"},"modified":"2025-01-29T23:13:19","modified_gmt":"2025-01-29T23:13:19","slug":"integrating-ai-into-research-may-revolutionize-outcomes","status":"publish","type":"post","link":"https:\/\/annualreports.healthsciences.arizona.edu\/2024\/integrating-ai-into-research-may-revolutionize-outcomes\/","title":{"rendered":"Integrating AI into research may revolutionize outcomes"},"content":{"rendered":"

\u201cResearchers in the field of health sciences are harnessing the power of artificial intelligence to revolutionize their approach to understanding and combating diseases. Across laboratories and institutions worldwide, AI algorithms are now not only assisting but often leading the charge in analyzing vast datasets, predicting patient outcomes and even uncovering novel therapeutic targets. This transformative partnership between human ingenuity and machine learning promises to reshape the landscape of health care, offering unprecedented insights and potential solutions to some of the most challenging medical mysteries of our time.\u201d<\/span><\/p>\n

That paragraph was not written by a person; the artificial intelligence application ChatGPT wrote it. And while allowing a large language model like ChatGPT to sort through interviews and synthesize the key points would make every writer\u2019s job easier, is it the ideal or ethical way to present research to an audience?<\/span><\/p>\n

\"\"<\/p>\n

\u201cAI has the potential to revolutionize teaching, research and problem-solving by enhancing education, advancing research capabilities and improving patient care outcomes,\u201d said\u00a0<\/span>Brian Ahn, PhD,<\/b>\u00a0dean of the\u00a0<\/span>University of Arizona College of Nursing<\/b><\/a>. \u201cEmbracing AI responsibly and ethically can lead to significant advancements in nursing practice and health care as a whole.\u201d<\/span><\/p>\n

Ahn is uniquely positioned to understand this impact. In addition to his\u00a0extensive nursing research, he has a Bachelor of Engineering degree in electrical engineering from the University of Seoul College of Engineering and a Master of Science degree in Electrical and Computer Engineering from the University of Florida College of Engineering. Ahn currently leads an NIH R01 study that integrates brain AI digital technology into pain and symptom management in older adults.<\/span><\/p>\n

\u201cThe rapid advancement of health care technology, such as machine learning and artificial intelligence, requires the integration of these new technologies into our education and research programs,\u201d Ahn said. \u201cOur college is in the process of establishing a new nursing engineering program and \u2018Center for Health and Technology\u2019 to incorporate computer technology into nursing education and research.\u201d<\/span><\/p>\n

It all starts with good data<\/b><\/p>\n

AI is a part of computer science that uses computers to do tasks that have historically required a human to complete, like problem-solving or simulating human capabilities, such as analyzing data or translating language. For researchers, sorting large data sets can be onerous work. But utilizing AI can cut that effort drastically.\u00a0<\/span><\/p>\n

While images of Skynet might come to mind for some people when the words \u201cAI\u201d and \u201csimulating human capabilities\u201d are combined in one sentence, the ability to sort through large amounts of information, seeking patterns or even holes in the data, can free up researchers to focus on other parts of problems.\u00a0<\/span><\/p>\n

\u201cMost of our research has been focused on assessing the current capabilities of AI or large language models,\u201d said\u00a0<\/span>Christopher Edwards<\/b>,\u00a0<\/span>PharmD,\u00a0<\/b>an associate clinical professor at the\u00a0<\/span>R. Ken Coit College of Pharmacy<\/b><\/a>.<\/span><\/p>\n

Edwards\u00a0and his colleagues\u00a0<\/span>Bernadette Cornelison, PharmD,\u00a0<\/b>and\u00a0<\/span>Brian Erstad, PharmD<\/b>,\u00a0recently worked on a project that examined the accuracy of Chat GPT in providing patient-facing information, particularly on common questions patients should ask their pharmacist when they fill a new prescription.<\/span><\/p>\n

The research assessed the output of the model for accuracy and completeness to see if it was generating quality information. It was looking to see if the AI was \u201challucinating,\u201d which is when an AI provides inaccurate or misleading information. The AI may have incomplete or incorrect data; there may be biases in the data or the old \u201cgarbage in, garbage out\u201d with false information in the data set.\u00a0<\/span><\/p>\n

\u201cIt can be very helpful writing learning objectives, test questions and editing,\u201d said\u00a0<\/span>Janine Hinton, PhD,<\/b>\u00a0an associate clinical professor and director of the Steele Innovative Learning Center in the College of Nursing.\u00a0\u201cBut you have to be very careful. It\u2019ll give you a reference that doesn\u2019t make sense. It\u2019s just hallucinating.\u00a0<\/span><\/p>\n

\u201cBut it will also present ideas that maybe I hadn\u2019t originally thought of and just help me get my work done faster. I know that there are people who really want to get it moving in health care, but there are challenges with confidentiality, with clinical decision-making. But I do think there are a lot of ways to blend it with other tools and our expertise to get our work done.\u201d<\/span><\/p>\n

Hinton, who is also a member of the\u00a0<\/span>BIO5\u00a0Institute<\/b><\/a>,\u00a0explained that the College of Nursing uses AI to model a patient in\u00a0<\/span>simulation training at the Gilbert campus<\/b><\/a>. The AI monitors and provides cues and clues to students to help them recognize interventions faster.\u00a0<\/span><\/p>\n

AI is much like gold mining<\/b><\/p>\n

Travis Wheeler, PhD,<\/b>\u00a0an associate professor at the\u00a0<\/span>Coit College of Pharmacy<\/b><\/a>\u00a0whose doctoral degree is in computer science from the U of A, compared AI to mining.<\/span><\/p>\n

\u201cThe power of AI comes from combining lots of training data with advanced techniques for learning to extract patterns from the data,\u201d he said. \u201cIt\u2019s a bit like mining. You might have a process that sifts through the dirt to extract big pieces of gold or minerals, but if there\u2019s nothing valuable in the dirt, you won\u2019t get anything out of it. That\u2019s like feeding bad data to an AI model, and is what we mean by \u2018garbage in.\u2019 But if the dirt has a ton of really useful stuff and your method only extracts the gold, there are still some useful rare earth materials that you tossed away because you were using bad technology. You would be missing other things that are in there.\u00a0<\/span><\/p>\n

\u201cWith better methods, you can extract more material out of that dirt. As AI methods advance, it\u2019s like building better mining methods, where you can extract more information out of the data you are given. It\u2019s not only the quality of the data but also the tools used to extract the information out of that data.\u201d<\/span><\/p>\n

Wheeler is a lynchpin at the U of A Health Sciences for AI work. He designs AI architectures\u00a0able to ingest data while accounting for biases or missing data, to allow the artificial intelligence models to learn to tell the difference between that hypothetical gold-painted rock and a real gold nugget. He has spent more than 25 years in research in designing algorithms, statistical models, and software for problems motivated by biological data.<\/span><\/p>\n

\u201cThe key idea behind AI and machine learning is that these models learn to perform classification or prediction tasks based on patterns extracted from the training data,\u201d\u00a0he said. \u201cThe challenge of the whole thing is both developing these large data sets that will provide the necessary information and then developing the kind of neat computational architectures that are capable of learning from those data.\u201d<\/span><\/p>\n

Beyond Chat GPT and crunching numbers<\/b><\/p>\n

But much like mining, recognizing when you have a gold nugget versus a gold-painted rock is important for researchers using AI.<\/span><\/p>\n

\u201cYou\u2019re taking data that is not completely vetted, not completely curated, so we have to learn how to mitigate bad-quality data,\u201d said\u00a0<\/span>Nirav Merchant<\/b>, director of the\u00a0<\/span>Data Science Institute<\/b><\/a>\u00a0and a member of the university\u2019s\u00a0<\/span>AI Access & Integrity Working Group.<\/b><\/a><\/p>\n

Any chef can tell you that your dinner is only as good as the ingredients you use. It\u2019s the same with using AI in research. But AI can move beyond crunching large data sets.\u00a0<\/span><\/p>\n

Allan Hamilton<\/b>,\u00a0<\/span>MD,\u00a0<\/b>the executive director of the\u00a0<\/span>Arizona Simulation Technology and Education Center<\/b><\/a>, is researching how\u00a0<\/span>AI can be used as a coaching tool<\/b><\/a>.<\/span><\/p>\n

\u201cAI should move the educational experience up almost to real time. It\u2019s coaching each individual exactly how they need to be coached,\u201d he said.<\/span><\/p>\n

One way Hamilton uses AI is through a bot that can respond in real time, using a variety of emotions, to help coach future physicians in medical interviewing. The second part of his research is finding ways AI can free up physicians.<\/span><\/p>\n

\u201cThirty percent of a doctor\u2019s time is paperwork,\u201d Hamilton said. \u201cWe know AI can do a lot of paperwork for us. How do we reapply that time? Hopefully the answer would be, you put it to good human use!\u201d\u00a0<\/span><\/p>\n

For instance, he described a scenario in an intensive care unit where AI is monitoring a patient.<\/span><\/p>\n

\u201cAI could make predictions about which patients were more likely to need rapid response, but it might also say the whole ICU team doesn\u2019t need to respond; you can send just two people,\u201d Hamilton said. \u201cIt ended up being 245% better at identifying who was likely to need rapid response than the hospital teams determined.<\/span><\/p>\n

\u201cIt\u2019s like, is it safer for me to be on the road with GPS and not looking around trying to figure out where I am going? Yeah, it is.\u201d<\/span><\/p>\n

Hamilton cautions, though, against health care providers relying too much on AI.<\/span><\/p>\n

\u201cI always say to students, \u2018Bots don\u2019t go to jail. Doctors do.\u2019 So, if a patient dies because a physician did precisely what a bot told them to do rather than what their training guided them toward, the human will be held responsible,\u201d he said.<\/span><\/p>\n

A good tool when used properly<\/b><\/p>\n

The researchers agreed that being transparent when AI or chatbots have been used in research is necessary for research integrity. As useful as it is to have AI write a draft of an abstract or study results, researchers need to be up front that it was utilized.\u00a0<\/span><\/p>\n

Justin Starren,<\/b>\u00a0<\/span>MD, PhD<\/b>, the director of the\u00a0<\/span>Center for Biomedical Informatics and Biostatistics<\/b><\/a>\u00a0at the U of A Health Sciences, compared relying on AI to his time in New York, where he lived on a wooded lot.<\/span><\/p>\n

\u201cThat meant I had a chain saw,\u201d he said. \u201cA chain saw is a great tool, but if you don\u2019t really understand how it works, you\u2019re probably going to get the nickname \u2018Stubby.\u2019 The current AI tools are like chain saws \u2013 they can cut through a huge amount of data really fast. And they can figuratively take an arm off equally as fast. They can be profoundly powerful, but profoundly stupid. The risk is that we know very well that people tend to believe computers,\u00a0even when they are wrong.\u00a0It\u2019s an extremely powerful tool.\u201d<\/span><\/p>\n

The issues of ensuring that high-quality data is being used, what the AI has been trained on and what tweaks were put into the system after it was trained are critical to minimizing racial bias or made-up answers.<\/span><\/p>\n

\u201cThese tools can be great proofreaders, great hypothesis generators and do universe matrix analysis to find the hole in the data, but we need to be transparent about their use,\u201d Starren added.<\/span><\/p>\n

\u201cI prefer to look at it as augmented intelligence rather than artificial intelligence,\u201d Merchant said. \u201cIf you know how to use it, you\u2019re going to be productive with it, but if you don\u2019t know how to engage with it, you\u2019re going to always try and find a nail for that hammer. So, stop thinking of AI as the hammer and just look where you can use it. Where can you use the automation that comes with some AI components?\u201d<\/span><\/p>\n

So much more to come\u00a0<\/b><\/p>\n

Merchant cautioned researchers that chat tools and large language models are only the tip of the iceberg when it comes to using AI in research.<\/span><\/p>\n

\u201cPeople are building really purposeful analysis methods and tools that are constantly coming out,\u201d he said. \u201cPay attention to those and see how we can use them because they will readily improve your science.\u201d<\/span><\/p>\n

For most of the U of A Health Sciences researchers, however, AI, or more specifically, Chat GPT, can\u2019t replace the human touch when \u201cswimming in the sea of language,\u201d as Starren put it. Often, AI-written content just doesn\u2019t read \u201chuman.\u201d<\/span><\/p>\n

\u201cI tried to use it to help write my wedding vows,\u201d Edwards said. \u201cAnd then I read it, and thought, \u2018This is mechanical garbage.\u2019 I don\u2019t want to sound like this, because this is terrible. It gave me a starting point, though, and spurred my creative juices.\u201d<\/span><\/p>\n

Much like the start of this story, ChatGPT was used to wrap it up as if it were writing it:<\/span><\/p>\n

\u201cAs AI continues to evolve and integrate into health sciences, its role as both a tool and a collaborator will only expand. The potential benefits are immense, from streamlining data analysis to enhancing patient care and education. However, the conversation around its ethical use and integration is equally crucial. As researchers and practitioners navigate this new frontier, they must balance the efficiency AI offers with the nuanced human touch that remains indispensable in healthcare. The ongoing challenge will be to harness AI\u2019s capabilities responsibly, ensuring that it complements rather than compromises the human elements of empathy, creativity and critical thinking.\u201d<\/span><\/i><\/p>\n","protected":false},"excerpt":{"rendered":"

\u201cResearchers in the field of health sciences are harnessing the power of artificial intelligence to revolutionize their approach to understanding and combating diseases. Across laboratories and institutions worldwide, AI algorithms are now not only assisting but often leading the charge in analyzing vast datasets, predicting patient outcomes and even uncovering novel therapeutic targets. This transformative […]<\/p>\n","protected":false},"author":3,"featured_media":2350,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[5],"tags":[],"college":[],"uahs_theme":[],"class_list":["post-2349","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-across-the-colleges"],"acf":[],"yoast_head":"\nIntegrating AI into research may revolutionize outcomes - University of Arizona Health Sciences Annual Impact Report 2024<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/annualreports.healthsciences.arizona.edu\/2024\/integrating-ai-into-research-may-revolutionize-outcomes\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Integrating AI into research may revolutionize outcomes - University of Arizona Health Sciences Annual Impact Report 2024\" \/>\n<meta property=\"og:description\" content=\"\u201cResearchers in the field of health sciences are harnessing the power of artificial intelligence to revolutionize their approach to understanding and combating diseases. 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