Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/2074/19979
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dc.contributor.advisorVenkatagiri, Shankar
dc.contributor.authorMitra, Neel Ratan
dc.date.accessioned2021-06-21T14:51:36Z-
dc.date.available2021-06-21T14:51:36Z-
dc.date.issued2019
dc.identifier.urihttps://repository.iimb.ac.in/handle/2074/19979-
dc.description.abstractMedical prescriptions are a rich source of data for Pharmaceutical companies & other stakeholders in the healthcare industry to gain insights on how their products & services are performing. For instance, as per the category of drug molecules being prescribed by doctors pharma companies can gauge the stage (growing, declining, etc.) of the life-cycle their drugs are at. Certain drugs molecules may be gaining favours across different specialty (e.g.: Cardiologist, Diabetologists, etc.) - being in possession of such knowledge would allow firms to realign their sales strategy to drive more drug prescription; and in turn generate more sales.
dc.publisherIndian Institute of Management Bangalore
dc.relation.ispartofseriesPGP_CCS_P19_107
dc.subjectArtificial intelligence
dc.subjectPharmaceutical industry
dc.subjectMachine learning
dc.subjectHealthcare industry
dc.titleApplying machine learning/Artificial intelligence in pharmaceutical data research
dc.typeCCS Project Report-PGP
dc.pages15p.
Appears in Collections:2019
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