AI Articles and Analysis about "Clinical support

A clinical decision support system (CDSS) is a health information technology system that is designed to provide physicians and other health professionals with clinical decision support (CDS), that is, assistance with clinical decision-making tasks.

Driving Patient Access and Decreasing Tech Debt in Healthcare with AI-1-min

Driving Patient Access and Decreasing Tech Debt in Healthcare with AI – with Aaron Chamberlain of Intermountain Health

Headquartered in Salt Lake City, Utah, Intermountain Health is a not-for-profit healthcare system comprised of 385 clinics and 33 hospitals dedicated to creating healthier communities and helping patients thrive. Intermountain Health merged with SCL Health in 2022 and now employs more than 58,000 people. They serve patients in Kansas, Colorado, Utah, Nevada, Wyoming, Idaho, and Montana.

AI Opportunities for
Life Sciences R&D-1

AI Opportunities for Life Sciences R&D – with Andrew Bolt of Deloitte

This interview analysis is sponsored by Deloitte and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

Automation and Beyond
for Sales and Marketing
in Life Sciences-1

Automation and Beyond for Sales and Marketing in Life Sciences – with Mark Miller of Deloitte

This interview analysis is sponsored by Deloitte and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

AI at athenahealth@2x

Artificial Intelligence at athenahealth

Athenahealth is a private healthcare company specializing in providing network-powered health services and point-of-care mobile apps. The company’s products and services are designed primarily to enhance patient care, improve operational efficiency and streamline administrative processes.

Improving Patient Experiences in Health Insurance Workflows@1x

Improving Patient Experiences in Health Insurance Workflows – with Shane Bray and John Thomas of Uniphore

This interview analysis is sponsored by Uniphore and was written, edited and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

Machine Learning and Large Language Models in Healthcare – with Dr. Arta Bakshandeh of Alignment Health@1x

Machine Learning and Large Language Models in Healthcare – with Dr. Arta Bakshandeh of Alignment Health

AI and machine learning have promising potential in the field of healthcare. However, there is one significant hurdle healthcare companies often encounter when trying to implement AI and machine learning. The data architecture of current legacy systems in healthcare settings prevents implementing many use cases and limits a company’s ability to benefit from these technologies fully.

The Impact of AI on Drug Target Discovery and the Personalization of Healthcare – with Leo Barella of Takeda@2x-min

The Impact of AI on Drug Target Discovery and the Personalization of Healthcare – with Leo Barella of Takeda

AI has profound implications for drug discovery, ushering in a new era of innovation and efficiency. Recent milestones - such as the first AI-designed drug molecule to enter human clinical trials and the prediction of protein structures for millions of proteins - showcase the transformative power of AI in this domain.

The Future of Patient Experiences in Healthcare – with Dr. Nele Jessel of Athenahealth@2x

The Future of Patient Experience in Healthcare – with Dr. Nele Jessel of Athenahealth

The healthcare industry has experienced several changes in recent decades. The Health Insurance Portability and Accountability Act (HIPAA), signed into law in 1996, represents one such change. HIPAA was initially intended to simplify how healthcare is administered. However, the law also contributed to the increased administrative burden for healthcare practitioners.