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Discover Emerging Practices in Healthcare Artificial Intelligence
This blog essentially functions as an exploratory study on new and emerging practices in the area of Artificial Intelligence and Healthcare. The ubiquity and rapid development of this field provides a perfect counterpart to health care technology, another growing sector. Advancements in Artificial Intelligence can help increase efficiency and accuracy in clinical decision support, interoperability, deep analytics, etc. This blog will provide news, studies, videos and other resources to help anyone understand the amalgam of these two fields. Use this website as a portal into the world of Healthcare Artificial Intelligence and the current development into improving the healthcare sector. Use the menu above to navigate between the various subcategories. Keep Learning!
Recent News
This section contains all the latest news and resources in the merger of Artificial Intelligence and HealthCare. The links in this section are also found in their respective categories above. Updates for this section will be regular. Explore the videos at the bottom of the page for more information and in-depth discussion.
Trial demonstrates early AI-guided detection of heart disease in routine practice
Read about new developments in early Artificial Intelligence guided detection for Heart Disease diagnoses. Funded by the Mayo Clinic’s Robert D. and Patricia E. Kearn Center for Science of Health Care Delivery, the ECG AI-Guided Screening for Low Ejection Fraction Study is using AI to detect Low Ejection Fraction Heart Disease using data from EKG results. This will facilitate diagnosis of patients in the real world especially since this type of Heart Disease (Low Ejection Fraction) is often difficult to diagnose, especially in its early stages.
Artificial Intelligence Enables Rapid COVID-19 Lung Imaging Analysis at UC San Diego Health
Read here about UC San Diego Health’s efforts to utilize Artificial Intelligence with Lung Imaging analysis to help diagnose hard to detect Pneumonia and as a result, COVID-19. Through a clinical research study, the physicians and radiologists at UCSD Health are able to augment lung imaging analysis X-rays with the help of AI. X-Ray imaging diagnostics can be useful in a pandemic as well as they are easy to clean, portable, and quick results.
Currently, only around 25% of providers are integrating AI technology into their data processing systems. -Dr. Tim Sandle
Leveraging AI and Machine Learning to Advance Interoperability in Healthcare
Interoperability is a vital part of the health care system. A lack of interoperability can inhibit data sharing. Without fluid data sharing between providers and partners, errors can occur and data can “fall through the cracks”. This article discusses using AI and Machine Learning to optimize Interoperability. This can help shift the industry from a fee-for service to a value-based model that provides the most value to the patient.
How Google Plans To Use AI To Reinvent The $3 Trillion US Healthcare Industry
Google is as synonymous with the internet as the words “browser” or “download”. Read here how Google looks to the future of healthcare by focusing on structured data and artificial intelligence. This article outlines Google’s plan of potential future expansion as well as its various and innovative healthcare initiatives currently or soon to be in development.
This article highlights the efforts being done at the University of Pittsburgh Medical Center to integrate natural language processing to make total use of the large swaths of unstructured data. Currently about 80% of all healthcare data is unstructured which means that the data is either not organized in any predefined fashion or it is of an unknown predefined model. These data sets are often extremely “text-heavy” meaning they can contain characters, dates, facts, numbers, etc. Read more below.
UPMC turns to NLP to make sense of unstructured data
How Machine Learning is Transforming Clinical Decision Support Tools
Read here to learn about the possibilities of using Machine Learning to transform Clinical Decision Support systems. In today’s world, Clinical Decision Support systems (CDS) have become crucial to any healthcare organization. Optimizing CDS systems can help to deliver optimal care but if integrated poorly, some CDS tools can become a hindrance. Find out more about this transformative process.
10 Promising AI Applications in Health Care
Read about the 10 Promising Artificial Intelligence Applications in Health Care currently being studied. The article discusses the use of AI technologies to optimize clinical and administrative health care processes. According to Rock Health, a leading venture capital firm, exactly 121 Artificial Intelligence and Machine Learning companies were able to raise $2.7 Billion in 2011 to 2017 from 206 deals.
This blog post at Health Fidelity by Chris Gluhak highlights how NLP has grown into becoming a buzzword among Health IT experts and decision-makers. He explains how the hype is backed up by the impact that AI and NLP will have on boosting administrative stability, quality of care and “support human experts”, as well. It is also part of the Health Fidelity’s series on NLP and Healthcare. Begin learning about how NLP actually works below
Illuminating Natural Language Processing in Healthcare
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This blog post at Health Fidelity by Adam Gronsky is an early installment of an ebook series called NLP in Healthcare: The Clinical FInancial Opportunity of Suspecting. The post explains how Health Fidelity’s “technology stack processes information” through their proprietary NLP engine, Lumanent Insights, to derive suspects. The term suspects refers to a “potential member conditions and treatments based on a wide variety of data sources to surface incomplete and under-documented diagnoses”. Learn more below.
Forward Looking Opportunities of NLP in Healthcare
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