The rapidly evolving healthcare landscape, driven by digital technology and AI, presents a pivotal moment for CMIOs and CIOs. The ONC's new HTI-1 rule, focusing on Decision Support Interventions, aims to set a standard for the development, implementation, and assessment of health IT, guiding the responsible integration of AI and digital tools in clinical settings. This blog post will walk you through everything you need to know.
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By leveraging vast amounts of data and advanced algorithms, machine learning allows us to make more accurate predictions, diagnoses, and treatment recommendations, and to identify patterns and trends that would be difficult for humans to detect. In this blog, we'll explore how machine learning is being applied in healthcare, the benefits and challenges of using this technology, and what the future of healthcare AI might hold. Whether you're a researcher, clinician, patient, or simply someone who is interested in the intersection of technology and healthcare, we hope this blog will provide valuable insights and spark your curiosity about this exciting and rapidly evolving field.
Just live, the Office of the National Coordinator for Health Information Technology's (ONC) metadata requirements have set a new certification standard that promotes transparency in DSI technology. "A DSI Intervention Checklist for Health Systems" provides a structured method to address the complexities of integrating DSIs. This approach ensures your health system not only complies with the latest regulations, but also maximizes the potential of these technologies to transform patient care.
Rare diseases affect 300 million people worldwide yet a thorough searching for success stories taking them on has returned few results. In an era of computational revolution and open source success, why aren’t there more? We will talk about why that is and what we at Health Universe will do to change that.
Physicians lose 30% of their time to administrative work aka not practicing medicine. Generative AI promises to solve this, but we’ve all heard stories of hallucinations and AI lawsuits. As the saying goes, you never want to practice with live ammo, so what is a physician to do? We will walk through how one physician uses generative AI in her personal life to learn how to use it in her professional one.
Physicians, nurses, and administrators spend far too much time on menial tasks. Generative AI promises to cure that. However, we in the healthcare industry have heard this all before. This white paper will lay out where the truth lies, why you should be truly excited, and where you should be a bit more skeptical.
Generative AI is everywhere. According to the Deloitte 2023 Health Care Consumer Survey, health care questions are one of the primary reasons that individuals are using generative AI. Although no everyone has used generative AI technology like chatGPT, over 80% of individuals have at least heard of it. Patients are using generative AI to learn about medical conditions, look at treatment options, and explore how to improve their well being. Early surveys suggests that patients that stand to gain the most from the use of generative AI models are those that lack insurance, or have less access to health care resources.
Today, a new startup called "Health Universe" announced the beta release of its platform that aggregates machine learning models for healthcare. The platform allows researchers to share clinical models with physicians, with a focus on improving outcomes in oncology.
There are several major trends in the field of healthcare machine learning that are worth noting. Here are some of the biggest ones:
As researchers, we are constantly seeking ways to make our work more accessible and useful to others. One way to do this is by converting our published scientific studies into interactive projects that can be easily used by others, such as physicians in a clinical setting. In this blog post, we will walk through the steps of how to convert a published scientific study into an interactive streamlit project that allows physicians to utilize a predictive model in a clinical setting.
Artificial intelligence (AI) is increasingly being adopted by physicians in a variety of settings, leading to significant improvements in patient care. According to a survey published in Frontiers, nearly 65% of physicians reported awareness of the application of clinical AI.
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