Machine Learning and AI in Healthcare Coming Up Short (Part 1)

An independent study on machine learning and artificial intelligence (AI) was released by the McKinsey Global Institute (MGI) in June 2017, focusing on the following central question: “Is artificial intelligence the next digital frontier, and if so, are businesses ready for it?”

(more…)

Getting the Most Out of Longitudinal Patient Data

Anonymous patient-level data (APLD) is data collected in real time from an individual patient. There has been an increasing interest in patient-level data, as researchers, healthcare providers, and pharmaceutical companies are realizing the potential of creating better comparisons of effective treatment outcomes by analyzing long-term data that represent individual patient-based experiences.

(more…)

Machine Learning and Healthcare: Breast Cancer Diagnosis, Part I

Machine Learning and Healthcare: Breast Cancer Diagnosis

(more…)

Top Use Cases for Machine Learning in Pharma


Real-World Use Cases for AI & ML in Pharma

For decades, Pharmaceutical data analytics has been a largely manual and tedious task conducted by the commercial research, health outcomes, R&D and Clinical Study groups at Pharma companies both small and large. With the emergence of machine learning, artificial intelligence and other disruptive innovations, Pharma, like other industries has also started its slow but sure transition to a more agile, data-driven model – one where in-house research is supplemented by intelligence gathered by applying algorithms across terabytes of Physician Rx, Patient Claims and other related datasets.

(more…)