Difference between revisions of "Artificial Intelligence"

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*[http://www.fathomhealth.com Fathom Health]: Applying AI and deep learning NLP to reimbursement. Formerly TinyRx (on-demand prescription delivery service, shut down in May 2016). Raised $7.7M. Google ventures included.
 
*[http://www.fathomhealth.com Fathom Health]: Applying AI and deep learning NLP to reimbursement. Formerly TinyRx (on-demand prescription delivery service, shut down in May 2016). Raised $7.7M. Google ventures included.
 
*[http://www.theneura.com Neura]: Using AI to optimize mobile apps and IoT devices for Med adherence. Interesting SDK approach. Raised $13M. Israeli team, located in Sunnyvale.
 
*[http://www.theneura.com Neura]: Using AI to optimize mobile apps and IoT devices for Med adherence. Interesting SDK approach. Raised $13M. Israeli team, located in Sunnyvale.
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*[http://www.enlitic.com Enlitic]: SF-based, $15M raised. Applying deep-learning to areas like triage, radiology, screening.

Revision as of 11:53, 30 March 2017

  • AI Cure: Applying machine learning and computer vision to medication adherence. Smartphone camera can verify if the patient took medication. Raised $15M+.
  • Atomwise: Drug discovery using AI. Raised $6M+
  • Cardiogram: Ex-google founders, applying deep learning to mobile health data. Backed by Andreessen Horowitz.
  • Recursion Pharmaceuticals: Drug discovery using AI. $13.2M in 3 rounds.
  • GNS Healthcare: Machine learning applied for precision medicine. Solutions around patient segmentation, drug discovery. $43M raised.
  • KenSci: Risk stratification of patient populations using ML. UW Tacoma professor founder. $8.5M raised.
  • Fathom Health: Applying AI and deep learning NLP to reimbursement. Formerly TinyRx (on-demand prescription delivery service, shut down in May 2016). Raised $7.7M. Google ventures included.
  • Neura: Using AI to optimize mobile apps and IoT devices for Med adherence. Interesting SDK approach. Raised $13M. Israeli team, located in Sunnyvale.
  • Enlitic: SF-based, $15M raised. Applying deep-learning to areas like triage, radiology, screening.