Sriya.AI Introduces Large Numerical Models (LNMs) to Optimize and Redefine Healthcare for Medical Groups

PRESS RELEASE
Published May 9, 2024


Atlanta, GA: Innovative AI solutions are entering the market daily, each offering detailed analytics and industry advancements. Among them is Sriya.AI, a group that is introducing the future of AI in the form of the AI Square algorithm (AI teaches AI to improve), a groundbreaking and innovative approach to machine learning built around the world’s first large numerical models (LNMs)—a numerical take on large language models (LLMs). Sriya.AI’s LNMs are designed to handle large numerical data with incredible accuracy, offering unparalleled solutions with input from localized datasets. With fast-learning AI that provides critical actionable insights and supports process improvements, Sriya.AI is poised to change the healthcare industry and global health solutions.

Quantifying healthcare is a core goal for the industry, with mathematicians and medical professionals working around the clock to accurately predict and define key metrics. Readmission rates, in particular, are a primary consideration for medical groups due to the potential impacts of unplanned readmission, which can place a drain on resources and create triage bottlenecks that strain staff and lower the quality of healthcare for patients. Sriya.AI’s systems, which currently span across 5 US provisional patents, can accurately identify a hospital’s less than 30 days readmission rate with 99-100% accuracy. Hospitals can then use this information to drastically improve their internal processes and prepare for vulnerable patients who may require more attention and care. For Sriya.AI, this is just the start.

“Large language models can help businesses in many ways but frequently give hallucination effects (glorified term for errors). Also, at the end of the day, numbers define business outcomes and are the true key to innovation,” says Srinivas Kilambi, CEO of Sriya.AI, citing numerical data as the main source of business improvements. “Large numerical models can help us use the past to drive decision-making in the present and better prepare for the future.” Every day, hospitals collect hundreds of data points for LNMs to learn from. By defining how these data points interact and what kind of outcomes they produce, predicting what comes next with a high level of accuracy is possible in many cases. Each hospital is unique, so applying a model that was trained on data similar to that hospital’s data can provide insights that generalized LLM predictions simply cannot match.

In addition to accurately predicting readmission rates, Sriya.ai is able to recognize and define other key metrics, like emergency triage rates, mortality rates and even an individual’s sepsis risk. By providing healthcare professionals with this knowledge, Sriya.ai helps medical teams to prepare for every outcome, empowering them to plan more effectively and take critical preventative actions that will allow them to better support the unique needs of the patients in their care.

With clearly defined insights and the ability to improve prediction accuracy by up to 100% in some cases, Sriya.AI is able to support daily operations in hospitals while offering significant advancements starting the moment a patient walks in the door. Triage, a critical component of hospital operations, can be drastically improved based on insights and information derived from AI Square. In a recent demonstration, Sriya.AI was able to accurately predict up to 50,000 ambulance requests with less than 150 false positives and negatives. These insights empower hospitals to improve their schedules, prepare for unexpected arrivals, and cut down on costs, as well as losses, caused by inefficiencies.

Behind Sriya.AI’s processes and improvements is a series of revolutionary artificial intelligence algorithms. This system optimizes AI using insights from the system itself, allowing it to learn and optimize on every level, leveraging data from each hospital to predict the flow of everything from emergency visits to stocking needs at each location.

To make the most of available data, Sriya.AI has its own defined methodology, which combines a scoring system with correlations to improve business outcomes in a wide range of circumstances. All variables are scored into a single Super Feature (SF) before being correlated directly with proven, data-backed business outcomes. Using AI Square to support detailed analytics, Sriya.AI numerically quantifies every documented variable within a hospital, allowing it to identify trends that are specific to the location rather than based on qualitative analysis from other hospitals with different sets of variables.

Process improvements for hospitals impact lives and families. With accurate information that can help medical teams improve their internal operations, hospitals can better serve their staff and their patients. From providing better healthcare to helping hospitals mitigate employee burnout–another key concern in healthcare–Sriya.AI is poised to change daily hospital operations and unexpected outcomes to help medical professionals better serve the public. In short, Sriya.AI can revolutionize hospital systems and patient care for the better.



Company: Sriya.ai

Contact: Srinvas Kilambi

Website: https://sriya.ai

Email: sk@sriyaai.com



Release ID: 1018952

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