Healthcare Technology Insights for Oct 1st — Oct 14th 2018
This fortnight, in the spirit of the #NHITWeek ,as expected a lot of curations were based around the Uses of Automation and Artificial Intelligence in Healthcare.
Here are our the top 5 insights by our experts on the stories from the past fortnight.
insights by Nrip Nihalani
Well how surprising! Collective human intelligence still works :)
As I been posting in my articles, speaking at my talks and offering my $0.02 in my insights, for all the talk of AI and Deep Learning, I feel technology’s best use in healthcare is in automation of processes and improving communication and collaboration between care teams. And such studies show that we have lots to gain by building better tools to help clinicians communicate and collaborate better. Someday , AI “may” replace human intelligence, but not today and not anytime soon.
Healthcare data is increasingly being analyzed. While we have written previously on AI, Prediction systems, automation, machine learning and other cool stuff, seemingly uncool technology is what provides the coolest benefits.
But this article and the story behind is the perfect example of how technology can be most effective for improving healthcare workflows in 2018 and 2019. Further ahead the benefits of the previously mentioned cool techs will hopefully be starting to be realizable, but we must use automation and analysis to intervene in current workflows and make them more effective today as much as we can.
This directly benefits clinical staff, speeds up care and actually starts making EHR data directly beneficial to those pained by the process of generating it.
To know about how many such benefits can be extracted from uncool technologies, check out our websites to learn about Medixcel and talk to us in the comments below.
eHealth literacy is the ability of internet users to locate, evaluate, and act upon web-based health information. The result of this study identifies that the role of “communication” in eHealth literacy remains underdeveloped.
Current frameworks and technologies do not account for physical and cognitive processing abilities necessary for multiway transactions.
A study of the Consumption(access by patients) patterns of a majority of patient education resources will be interesting. It may shed light on this underdevelopment being required or not.
DeepMind furthering AI cancer research program with new partnership in Japan to refine breast cancer detection algorithms
Healthcare data is increasingly being analyzed and complex algorithms created to help various aspects of the healthcare ecosystem.
A big problem is the availability of huge data sets, and where available, the prevention of their misuse.
Its great that Deepmind is able to source data sets , (being a sub of Google, am sure plays a role), and hopefully they will put their deep mind ;) to good use and be able to improve detection algorithms.
Its also promising that Tencent has already been working on computer vision software that can diagnose skin cancer from pictures taken with a phone, and its AIMIS system already has the capability to detect esophageal cancer, lung sarcoidosis, and diabetic retinopathy from medical images
I have written previously on this, and it will be useful for patients and if the data sets do help create both faster as well as more accurate detection algorithms in the future.
I feel an upcoming market sometimes needs exposure so others can see opportunities to help, invest and mentor the growth there. I felt there are tons of new opportunities for so many of this blogs readers when I was reading this, and so I felt it would be useful to share.
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