Healthcare documentation processes are still heavily paper-based, which is tedious, error-prone, and time-consuming. Manual data entry and reliance on physical documents slow down healthcare delivery and can lead to inaccuracies that affect patient care.
View SolutionMany businesses struggle to integrate data from disparate sources, which is a significant challenge to real-time analytics and AI adoption. Building and maintaining these capabilities often requires significant investments in talent, technology, and infrastructure, leading to slow time-to-value.
View SolutionLegacy database systems can be a significant blocker to organizational agility and growth. As they were often designed for a different era, they can be struggling to handle the exponential growth of data in today's digital world. Adding new data can become difficult and slow, affecting performance and limiting your ability to adapt to changing business needs.
View SolutionCloud-based simulations to predict failure of equipment and improve the efficiency of maintenance operations
Reducing patient falls — a billion dollar cost to the healthcare system, can be combatted with help of Kubernetes Engine
Medical devices and robotics company leverages machine learning to launch predictive models to classify the level of responsiveness of in-home neurological recovery therapy
85% of machine learning models end as experiments. Don't take chances, work with Bitstrapped to avoid the pitfalls and blindspots at the (3) stages of the machine learning journey:
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