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Why Providers Should Centralize Analytics

In this special guest feature, Hossein Fakhrai-Rad, President & Chief Scientific Officer at BaseHealth, discusses how In the future, the insights derived from centralized analytics delivery models are likely to help hospitals improve quality, lower costs, identify at-risk populations and better understand performance. For that to happen, however, hospitals and health systems must first overcome the fragmented, decentralized approach to analytics that prevents them from realizing the full value of their analytics investments.

Automated Compliance Technology is the Key to Quality Health Data Analytics

In this special guest feature, Guy Meger, CTO, VP R&D of EarlySense, (a leader in contact-free, continuous monitoring solutions for the healthcare continuum) discusses how with automated compliance monitoring in place, healthcare staff can focus their expertise and time on healing, while patients can rest and recuperate without any anxiety-induced disturbances. For these reasons, many global hospitals and medical facilities are turning to automated compliance technology to support big data systems that operate at their full potential and reach their clinical and economic goals.

How Big Data Helps Vaccines Improve

In this contributed article, freelance human Avery Phillips believes that the possibilities with big data and vaccinology are endless. Lists could be automatically generated to identify under-vaccinated populations, determining what vaccines are overdue, and giving reminders to doctors and the public. Systems such as these might be the best use of big data in the quest of delivering holistic and safe health to people around the globe.

Coding the Cure for Cancer

In this special guest feature, Emily Walsh, the Community Outreach Director for the Mesothelioma Cancer Alliance, discusses how artificial intelligence is helping to detect cancers as well as the role AI is playing in the processing and sorting of data collected by cancer researchers.

How Big Data is Helping Monitor STD Rates and Get People Tested

In this contributed article, freelance human Avery Phillips discusses the importance of tracking data around infection rates, geographical location, and patient demographics for the continued treatment of STDs. This not only helps us understand how changes in communication will need to be made but also what populations need to be informed so that they can better understand their treatment. Managing big data like this and finding ways to implement it is where tech companies can step in to help with current STD rates and treatments.

Why AI is the Future of Prior Auths

In this contributed article, Ron Wince, Founder/CEO of Myndshft, examines the healthcare industry in light of a powerful argument to be made that both provider organizations and health plans can reap immediate, transformative results with AI by breaking ground on the business and administrative side of healthcare. Optimizing the prior authorization process is perhaps the most compelling example.

What’s Next? Learning Communities in AI and Healthcare

Artificial intelligence is making a difference to healthcare, right now. For more information on how to get involved in this important and growing sector, take advantage of the resources outlined in this post, including the Dell EMC Machine Learning Knowledge Center, Dell EMC Customer Solution Centers and the Deep Learning Institute by Dell EMC. These have been created for the purpose of sharing expertise and offering guidance for those interested in deep learning.

Finding a solution for AI in Healthcare

Dell EMC Ready Solutions for AI are integrated systems with validated hardware and software stacks optimized to accelerate AI initiatives, shortening the time to architect a new solution by six to twelve months. A new insideBIGDATA special report series explores the intersection of AI and medicine, and this entry provides a series of solutions for AI in healthcare, including Dell EMC Ready Solutions for AI.

From Safari to the Stratified Medicine: How Machine Learning Connects the Dots to Create a Future Health Trajectory

In this contributed article, Ori Geva, the Co-Founder and CEO of Medial EarlySign, describes a clear parallel between the work of the professional animal tracker and the use of machine learning in healthcare. Both share the ability to harmonize data to tell a potentially meaningful story. Through both experience and inherited learning, they know how to identify and connect the dots.

AI in Medicine: Developments in Radiology, Genomics & Diagnostics

Next-generation radiology tools may remove the need for tissue sampling and greatly expand the area of delivery. And the translational Genomics Research Institute’s (TGen) Center for Rare Childhood Disorders is using machine learning for genetic sequencing. Part of an insideBIGDATA special report series on AI and healthcare, this entry highlights some of the latest developments in AI in medicine, including progress in radiology, genomics and diagnostics.