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http://ai-pharma.com/event-guide/

https://linkstream2.gerstein.info/tag/i0aibos/

https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/1471-2288-13-61

Comfort cites classic work by P Meehl: Clinical v Statistical
Prediction https://books.google.com/books/about/Clinical_Versus_Statistical_Prediction.html #AIPharma @AIPharma_Summit

https://sv.ai/hackathon/

https://www.slideshare.net/mobile/ShaunComfort

https://www.ucsf.edu/news/2017/07/407661/ucsf-cancer-researcher-leads-team-win-first-ever-ai-genomics-hackathon

http://www.xconomy.com/san-francisco/2017/06/23/startup-founders-quest-for-cure-leads-to-genomics-hackathon-at-google/

Please find the article at link:
https://www.pharma-iq.com/informatics/articles/is-big-pharma-really-on-cusp-of-ai-shake-out-0

Is big pharma really on cusp of AI shake-out?

By: Pharma IQ
Posted: 07/14/2017

QT:{{”

The promises of “disruptive technologies” have failed to live up to expectations in the past. For example, the development of ‘high throughput screening’ – a process that employs robotics to conduct millions of chemical, genetic and pharmacological tests in rapid time – in the 1990s failed to significantly reduce R&D inefficiencies and offered sporadic success rates.

“The major cost in drug R&D is last-phase clinical trials,” said Dr Mark Gerstein, professor of biomedical informatics at Yale University. “It is not clear whether AI can be as useful for these as it has been in target selection for the initial phases.”

“One of the first principles of data mining is that history is a good predictor of the future. AI has a track record of not living up to its expectations and therefore caution about how great its impact will be in the healthcare industry is now warranted.”
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