This is the guy behind the guy behind the guy. | Talking technology, enterprise, medical, music, & sports | Founder/CTO/President of @ENHATCH
Joined July 2008
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Join this exclusive webinar featuring Michael Phipps @uberphipps President of Enhatch, and Kerim Genc of @Simpleware_SNPS.
Date: 07/17/24
Time: 11 AM - 12 PM EDT
Registration Link: bit.ly/4d2jJb4
Can't attend? Register anyway to get the link to the recording.
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Imagine automating manual steps and significantly reducing the time needed to generate patient-specific guides using just #xrays or CT images! That's just something our Intelligent Surgery software helps with. Connect with us at #AAOS2024 using this link bit.ly/3Skzy4v
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We are excited to announce the U.S. FDA 510(k) clearance of a patient-specific instrumentation system for Total #Knee #Arthroplasty. Meet us at Booth #5245 at #AAOS2024 to learn more. Click here to read the Press Release: blog.enhatch.com/510k-cleara…
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2024 trends in Orthopedics! Read our latest blog on how #AI can transform preoperative planning in #orthopedics and deliver great efficiencies for medical device companies, surgeons and the entire healthcare system. bit.ly/3S3fl4c
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27 Mar 2023
Fascinating research reveals a machine learning-based pipeline for designing custom knee replacement implants, automating the process while maintaining accuracy. A leap towards more personalized medicine! :rocket::brain: #innovation #healthcare #AI
nature.com/articles/s41598-0…
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Phipps retweeted
25 Mar 2023
It was a HUGE week in generative AI:
• Google Bard
• Adobe Firefly
• Bing Image Gen
• Github Copilot X
• ChatGPT plugins
• Generative Canva
• Roblox Generative
• Nvidia DGX Power
• Runway Text-to-video
• Microsoft’s Notion killer
Here’s what you need to know.
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30 Dec 2022
Great to see end-to-end workflows that actually make sense
23 Dec 2022
Mass General Brigham will be among the first to accelerate end-to-end AI model development and deployment in clinical workflows using #MONAI and #NuancePIN. #RSNA22 Read the press release: nvda.ws/3u9FoKm bit.ly/3GeAW3x
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Phipps retweeted
14 Oct 2022
THREAD: The US government's new export controls are wreaking havoc on China's chip industry.
New rules around "US persons" are driving an "industry-wide decapitation."
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Phipps retweeted
7 Sep 2022
"Self-Supervised Pretraining for 2D Medical Image Segmentation"
How should you pretrain your model if your goal is maximizing downstream segmentation quality? [1/9]
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Phipps retweeted
5 Dec 2021
Alright, I'll be giving away this $10,000 Gucci XBox to a follower who retweets this in the next 24 hours. I'll ship it anywhere on earth. Good luck.
Here's what's inside: youtu.be/JnGXTk57rOU
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Phipps retweeted
16 Nov 2021
Intelligent Surgery is the disruption that medical device companies need in order to be competitive. Learn how your company can increase revenue and productivity by embracing new technologies in a free e-book
ow.ly/fxbP50GP3jw
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Distilling Image Classifiers in Object Detectors
abs: arxiv.org/abs/2106.05209
github: github.com/NVlabs/DICOD
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I have been told that @Esquire has lifted the paywall on "The Falling Man" so I'm posting the link. Thanks all.
esquire.com/news-politics/a4…
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⚡BIG⚡announcement from Enhatch at AAOS 2021!
Stop by our booth # 235 tomorrow and become immersed in the Intelligent Surgery Ecosystem. #orthopedics #surgery #aaos2021 #AI #HealthTech #OrthoTwitter
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Wonder how proven techniques merge with cutting edge technology? Join us during this year's annual meeting as Leo Whiteside, MD. will discuss how AI can make his technique smarter, faster, and safer. #AAOS2021 #OrthoTwitter
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Phipps retweeted
6 Aug 2021
✍️ How to build a Deep Learning system that will answer questions about the Harry Potter universe?
A tiny Q&A project I built using RIVA from @NVIDIAAI in combination with a @huggingface model!
radekosmulski.medium.com/how…
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Phipps retweeted
8 Jul 2021
Dataset bias strikes again! 😬
This is a great example of dataset bias! This ML method classifies skin lesions as being malignant or not.
Can you see the problem from the examples? 🤔
Let me shortly explain 👇
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Production machine learning is disappointing for many.
People feel cheated when they realize that 90% of their work is dealing with data, and most of the remaining time focuses on engineering work.
I know you were expecting fancy math formulas everywhere. Sorry about that.
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