While Speech Recognition was a definite and necessary building block that made Natural Language Processing (NLP) ultimately possible, equating it with NLP is like comparing a 1921 Model T Ford with a 2021 model, self-driving Tesla.
What does Frankenstein have to do with health IT consolidation? Are IT professionals more like Indiana Jones or McGyver? Is there an end in sight to the consolidation trend?
Is AI a threat to physicians? Is it possible for AI algorithms to make physicians obsolete? Will the robots take over? In the second part of this series, Florent Saint-Clair kiboshes some of the many fears associated with AI. And highlights the many advancements the merging of AI and healthcare has benefitted the industry.
Florent Saint-Clair challenges the healthcare community to let go of lingering fear or doubts and accept that in 2021 AI is here to stay.
Artificial Intelligence (AI) in healthcare imaging is at an inflection point. Despite the growing body of evidence that shows the promise of AI in healthcare, radiology is adopting AI with some hesitation. AI algorithms made available strictly as a cloud solution exclude many healthcare organizations that have not adopted the cloud.
While Speech Recognition was a definite and necessary building block that made Natural Language Processing (NLP) ultimately possible, equating it with NLP is like comparing a 1921 Model T Ford with a 2021 model, self-driving Tesla.
What does Frankenstein have to do with health IT consolidation? Are IT professionals more like Indiana Jones or McGyver? Is there an end in sight to the consolidation trend?
Is AI a threat to physicians? Is it possible for AI algorithms to make physicians obsolete? Will the robots take over? In the second part of this series, Florent Saint-Clair kiboshes some of the many fears associated with AI. And highlights the many advancements the merging of AI and healthcare has benefitted the industry.
