Mendel Launches Hypercube, An Ai-copilot For Real World Data Applications

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Mendel, a pioneer in clinical AI technology, has unveiled "Hypercube," a cutting-edge AI copilot made to make patient data analysis easier for life sciences and healthcare institutions. Organizations may access and comprehend both organized and unstructured patient data with Hypercube's user-friendly chat-like interface, which facilitates quick insights and answers to issues that were previously unanswerable.

Large language models (LLMs) and neural networks, two machine learning techniques, are the mainstays of traditional AI approaches for health data processing. These techniques, however, frequently fail to grasp the subtleties of clinical language and can result in erroneous or unpredictable results. In order to overcome this difficulty, Hypercube employs a proprietary hybrid technique that blends symbolic AI and massive language modeling, enabling users to ask intricate cohort analyses in simple terms. Additionally, sophisticated users—such as data scientists—have the ability to display queries and employ programmatic tools for analysis, which broadens the platform's application across various departments within ...
... a company.

Mendel's co-founder and CEO, Dr. Karim Galil, highlighted the importance of Hypercube by pointing out that it marks a significant advancement in real-world data (RWD) applications. The technology not only overcomes the drawbacks of traditional data searching techniques like structured query language (SQL) and software-as-a-service (SaaS), but it also does away with the necessity for labor-intensive procedures to unlock unstructured data.

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