Image by freepik
What You Should Know:
– Carta Healthcare, a provider of clinical data solutions, recently conducted a survey of clinical data abstractors to understand their perspectives on the use of AI in their profession.
–…
Continue Reading
While AI can offer immense potential to improve patient outcomes and streamline medical processes, system flaws can pose risks to ethics, security and data accuracy.Dr Gao Yujia, assistant group CTO of the National University…
Continue Reading
What You Should Know:
– Cornerstone AI, creators of a powerful AI software solution that cleans real world healthcare data significantly faster and more accurately than existing solutions, today announced that healthcare technology company Komodo Health…
Continue Reading
What You Should Know:
– Incorrect data in health plan physician directories is a pervasive problem, according to new research conducted by researchers at University of Colorado and HiLabs.
– The study, published in BMC Health…
Continue Reading
This roundup will be published monthly. It is meant to highlight some of the most notable funding rounds of the month and is not intended to be comprehensive.
Several major fundraising announcements in the payer/employer…
HiLabs, a company that uses AI to manage dirty data, has raised $39 million in Series B funding, the company announced Thursday.
Bethesda, Maryland-based HiLabs was founded in 2014 and primarily serves health insurers. Its…
The following is a guest article by Ann Krutsko, Healthcare IT Researcher at ScienceSoft
In healthcare, working with inaccurate patient data is a dangerous game. Electronic Health Records (EHRs) were designed to streamline operations and…
Kel Pults from Mediquant addresses issues like data security, suggesting practical strategies such as reducing IT footprints. She also highlights the importance of single patient identifiers, crucial for ensuring data accuracy in an era…
Continue Reading
Enlitic and Infinitt join forces, integrating Endex data standardization into Infinitt’s PACS. This collaboration targets medical imaging data standardization, leveraging AI technology to enhance radiology workflow efficiency. It resolves interoperability issues, ensuring consistency, reliability,…
Continue Reading
One of the biggest problems with AI solutions in healthcare right now is getting quality data that you can use to train your AI models. When you train an AI model using generic data,…
Continue Reading
