How is Machine Learning being used in treatment of rare diseases?

The arrival of machine learning (ML) and its associated abilities have created numerous possibilities for intelligent intervention, which, if leveraged perfectly, can significantly help in treating rare diseases. Want to know how? keep reading.

Rare Disease Facts

Challenges in Treatment of Rare Diseases

The lack of scientific knowledge and quality information on the disease often results in a delay in diagnosis. Due to the broad diversity of disorders and relatively common symptoms which can hide underlying rare diseases, initial misdiagnosis is common. In addition, symptoms differ not only from disease to disease but also from patient to patient suffering from the same disease.

Using Machine Learning for Treatment of Rare Diseases

Summary

Reading the right kind of data, deriving actionable insights, and combining them into a sustainable people-driven operational plan is the only way for life sciences organizations to demystify rare diseases. A better knowledge of patient journeys will proceed to compress (and strengthen) disease diagnoses. Life sciences companies require to operate closely with healthcare stakeholders to involve patients in their diagnostic cycles. With proper data and assisted technology, patients and physicians can act together to create better treatment opportunities, and improved patient lives. The beginning of Machine Learning and its infinite sea of computing opportunities have inspired life sciences companies to adopt the fourth industrial revolution. With this, the trifecta of data, technology, and people, promises to cut bigger healthcare walls, as it has in the past.