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Revamping the healthcare sector with data science expert Rohan Singh Rajput

A gradual yet comprehensive revolution is underway in the continuously evolving healthcare landscape, all thanks to machine learning. Technology has turned the healthcare industry upside down in terms of predicting patient outcomes and optimising hospital operations, and this is just the tip of the iceberg.

Rohan Singh Rajput is a seasoned data scientist with a rich history of deploying machine-learning models in various industries. He has a revered record of collaborating with pharmacies and hospitals to create predictive models for patient risk scores by remarkably using Electronic Health Records (EHR) and census data. Through Rajput’s work and expertise in the field, we try to gauge the current trends and the needs of this industry.

Rajput has been a driving force in bringing about fundamental changes in this industry. Leveraging the EHR and census data, Rajput, along with his colleagues, worked on the development of models that can predict patient risk scores, which are crucial in determining the kind of care a patient might need in the future, allowing healthcare providers to be better prepared and allocate resources more efficiently.

He has also worked diligently on the enhancement of a rule-based model to an ensemble machine-learning predictive model using regression and XGBoost. This upgrade has led to a remarkable improvement in patient adherence, which ensures that patients are more likely to follow medical advice, take prescribed medications, and reduce potential health complications. Apart from enabling better patient health outcomes, this also translates to reduced costs for healthcare insurance providers.

Beyond that, Rajput’s expertise also encompasses preprocessing data, applying statistical modelling to extract sensitive information from EHR data, and extracting patterns from hyper-dimensional census data. He has instrumentally contributed to the reduction of feature space, optimal data management, and attainment of actionable insights with t-SNE, UMAP, FAMD, CCA, and randomised SVD, all of which are dimensionality reduction methods used for decoding super complex data.

As crucial as these contributions seem, their impact goes way beyond. Predictive models like the ones developed by Rajput allow healthcare providers to anticipate the needs of the patients, because of which medical personnel, equipment, medications, and other resources are allocated where they are needed the most, reducing wastage and ensuring timely care. Additionally, patient adherence reduces the risk of health complications and the need for expensive interventions. This also allows hospitals to function at their optimal capacity with decreased overhead costs.

Data science is one faculty that is revamping almost every other industry or domain, while, data-driven approaches of professionals like Rohan are at the top, ensuring that technology is harnessed to its fullest potential for the betterment of society at large.

Mohsin AL Moharrak is a business journalist.