Bio International Convention – Media Advisory

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MEDIA ADVISORY

Bio International Convention

BioSymetrics to present at #Bio2019

BioSymetrics CSO Gabe Musso to Present on Artificial Intelligence and Machine Learning for Biomedical R&D Innovation at the 2019 BIO International Convention

PHILADELPHIA – (June 3, 2019) – Biomedical artificial intelligence (AI) company BioSymetrics will offer a presentation on the use of AI and machine learning for healthcare and biomedical R&D innovation at the 2019 BIO International Convention, which is being held June 3-6 at the Pennsylvania Convention Center in Philadelphia. The company’s Chief Scientific Office, Gabe Musso, will lead the presentation on Wednesday, June 5, at 11:15 am, in Theater 3. Read More

Meet us at Bio 2019 | Take a Walking Tour of Philadelphia

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Bio International Convention

Bio International, Philadelphia June 3-6

Our own Gabe Musso, CSO of BioSymetrics will be presenting how Augusta™ is being deployed to increase the speed and confidence of machine learning and AI in biomedical use cases.

BioSymetrics
Theater 3, Level 200
Wednesday From 11:15 AM To 11:30 AM

Looking for something different in the evening?

Why not get out and walk with us as we take a short tour of the historical Society Hill/Olde City section of Philadelphia including the Betsy Ross House, Liberty Bell, Independence Hall, and Head House Square. You can be sure we will end the short walk with a cheesesteak at iconic Jim’s on South Street.  (Our CMO grew up in Philly and swears it is better than Pats or Geno’s.)

RSVP for our Bio2019 Event

MEDIA ADVISORY: BioSymetrics to Demonstrate Usage of Artificial Intelligence for Healthcare and Biomedical R&D Innovation at Collision 2019

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TORONTO – (May 21, 2019) – Biomedical artificial intelligence (AI) company BioSymetrics will be attending Collision 2019, which is being held May 20-23 at the Entercare Centre in Toronto. BioSymetrics is pioneering proprietary data science and machine learning software in order to best optimize medical discovery and life sciences productivity.

The company’s Chief Scientific Officer, Gabe Musso, will be available for meetings at Collision during the HealthConf track on Thursday, May 23, at BioSymetrics’ booth (Booth #B101) and can discuss how BioSymetrics’ inaugural product, the Augusta™ software platform, provides a holistic solution to some of the current industry challenges, including the utilization of good data without bias to feed machine learning models, as well as solving the ability to interrogate multiple models. BioSymetrics simplifies biomedical data science projects by reducing the time spent on data pre-processing, thus ultimately helping to build more effective predictive models that enable solutions to reach the market more quickly.

NOTE: Booth #B101 will be located in a different area on Thursday; please ask for directions at the information desk.

Media & Analyst Briefings

To schedule a briefing with BioSymetrics at Collision, please contact BioSymetrics’ PR team at 774-551-6679 or kgrill@elevatecom.com.

About BioSymetrics

For additional information, visit http://biosymetrics.com.

 

Media Contacts:                    

Korie Grill, Account Executive

Elevate Communications

kgrill@elevatecom.com

FDA developing new rules for artificial intelligence in medicine

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It’s very encouraging to see the FDA showing forward thinking when it comes to AI/ML-based diagnostics. Even the best model can be outdated quickly given the changing data landscape, making frameworks like Augusta that allow for model refinement and evolution to be crucial. We welcome this mindset as we work with our partners to build more interpretable and more adaptable diagnostic models.

FDA developing new rules for artificial intelligence in medicine

‘Contingent AI’, What is it?

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Machine Learning with ContingentAI
What is Contingent AI? 

In any data science pipeline there are a number of options that are selected for data processing (e.g. contrast settings for medical images, data imputation approaches, bandpass filter cut-offs for ecg signals). Typically, these options are selected manually based on previous experience of the Data Scientist or recommendations from previous, similar studies. In contingent AI, any “settable” parameter for data processing, data integration, or feature selection is permuted and the corresponding effects on the downstream predictive model measured. This process is similar to hyperparameter tuning in machine learning, however instead of optimizing only the machine learning model, the entire data science pipeline (including model selection) is subject to optimization.

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