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Discover Emerging Practices in Artificial Intelligence

Clinical Decision Support

In this section you will find more specific resources regarding Artificial Intelligence and the vital concept of clinical decision support. In healthcare technology, clinical decision support (CDS) is defined as the system that provides physicians, clinicians, etc. with information and knowledge that is either individual specific or filtered through intelligent means and presented at specified/appropriate times. The recent evolution of AI merges perfectly with this type of system decision making processes. Artificial intelligence and machine learning both improve the quality of the data thus produce largely accurate and clean results ensuring compliance with regulations. For example, you can find links to Apixio blog posts that discuss machine learning and artificial intelligence clinical applications and support systems. Explore the videos at the bottom of the page for more information about IBM's Watson and more  as well as further in-depth discussions.

A look at operational and clinical applications of AI in healthcare

The deployment of artificial intelligence as augmented intelligence has numerous benefits especially within the healthcare setting. Through the use of augmented intelligence doctors and nurses are given access to quick and accurate recommendations that are data-driven. The use of AI can provide professionals with treatment options as well as solutions to diagnostic questions that are based on often very large data sets of similar cases. Read this article that discusses the utilization of Artificial Intelligence with operational and clinical applications.

Artificial Intelligence: A Primer for Healthcare Decision-Makers

This primer provides you with the necessary information that is designed specifically for healthcare industry decision makers that also need a “fundamental” understanding of Artificial Intelligence. This post will allow industry leaders to “keep up” with news as well as evaluate potential vendor solutions that involve artificial technology. Continue reading on Apixio through the link below.

A common roadblock that occurs with using clinical data for risk adjustment is that most if not all, risk adjustment experts do not have expertise in analyzing or collecting data, especially large quantities. This blog post highlights this issue and provides solutions using AI and NLP technologies. Read more on why clinical data contains the greatest details about health that can be obtained through NLP analytics.
 

Why Clinical Data is a Critical Aspect of Risk Adjustment

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.

This post provides insights into how artificial intelligence technologies coupled with clinical decision support will help to facilitate doctor patient facetime. This post features comments from Anand Shroff, Chief Development Officer and founder of Health Fidelity. He discusses some challenges and obstacles that can occur such as cost and time for implementation. He also touches on the existence of an “innate fear that advance automation in healthcare reduces patient-provider interaction”. Find out more below

How AI Technologies Will Create More Doctor-Patient Face-time

Apixio Launches HCC Complete to Support Accurate Risk Adjustment

This informatiative press release issued by Apixio highlights its new use of its proprietary artificial intelligence Platform technology, HCC Complete as a tool for risk adjustment solutions. HCC Complete uses AI to “support a comprehensive chart review experience”. In essence it identifies any potential missed and unsupported acute and chronic conditions that were previously reported and can be used for risk adjustment. Read up further on Apixio’s site through the link below

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 as well as 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 to produce results.

Watson Health is smarter health

Exploring the Risk Adjustment Continuum

How Machine Learning is Transforming Clinical Decision Support Tools

Change Healthcare to Provide Free Healthcare Data Interoperability Services for All Americans on Amazon Web Services

1.2.1 The Analytics Edge - Video 1: Introduction to The Analytics Edge
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Ray Kurzweil (USA) at Ci2019 - The Future of Intelligence, Artificial and Natural
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Andrew Ng - The State of Artificial Intelligence
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AI FOR GOOD - AI and Medicine
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Get to the why with the all-new IBM Cognos Analytics
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