Sindhu Adini

The Race for Vaccination: How SpringML Helps Accelerate State Vaccine Rollouts

With the announcement of a third approved COVID-19 vaccine, the race to achieve mass vaccination is officially in full swing. SpringML is proud to play a role as we help states across the country implement Google Cloud's Intelligent Vaccine Impact solution. Time is of the essence for anything related to the vaccine and our agile approach …

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The Race for Vaccination

AI Powered Medical Imaging Solutions

Navigating the pandemic forced many companies to pivot to a digital-first strategy, with telehealth and telemedicine receiving a lot of attention in 2020. The future of medical imaging solutions using AI holds great promise for saving lives, improving productivity, and reducing costs. Watch the on-demand webinar to learn about the AI Powered Medical Imaging Solutions. We’ll …

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AI-Powered Medical Imaging Solutions

Campus Reopening Solutions for Higher Education with Google Cloud

In this podcast, Google Cloud’s Chris Haas, SpringML’s Sindhu Adini and Washington University in St. Louis’s Dr. Philip R.O. Payne discuss how a data-driven approach can help drive efficient campus reopening solutions for student and faculty wellness. Listen to this podcast to hear insights on: How to implement contact tracing and symptom checks Vaccination eligibility and …

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Vaccine Allocation and Distribution

The upcoming phase of the distribution of developed vaccines for COVID-19 comes with its own set of operational and distribution challenges. In addition to the high margin of error and issues in supply chain management, demand-supply analysis and tracing of the administered vaccine, there is a bigger challenge to administer the vaccine at a large scale, …

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Vaccine Allocation and Distribution

Patient 360 Analytics for Providers

Patients today expect consumer grade experience from their providers. They expect efficiency in any interaction with a hospital – all the way from registration to physician interactions and finally to billing. Patients are also very informed of medical conditions, treatment options and risks, and expect high value personalized care from physicians. According to some estimates, 82% of patients would switch providers after a bad experience. Providers are looking at innovative ways to meet these expectations and keeping patients satisfied.

Patient care

Leveraging ML to Enhance Productivity in the Life Sciences Industry

With costs soaring and business models predicated on continued innovation, life sciences firms are searching for greater efficiency and agility. One of the most promising ways forward lies in harnessing the power and potential of machine learning (ML) tools. This Whitepaper considers several ways in which life sciences firms can use machine learning to favorably impact R&D productivity, clinical efficacy, and supply chain efficiency.

Leveraging ML to Enhance Productivity in Life Sciences