2024 - Real-World Data 2.0: Decoding Patient Journeys at Scale Using Clinical AI
Date2024-04-29
Deadline2024-04-29
VenueONLINE-VIRTUAL, USA - United States
KeywordsLife Sciences; Healthcare; Commercialization & HEOR
Topics/Call fo Papers
While generative artificial intelligence (AI) is revolutionary, experts acknowledge that deep learning alone cannot achieve true human-like reasoning. Issues like the explainability of AI decision-making make it difficult to adopt general domain large language models (LLMs) for areas like medicine where correctness can be a matter of life and death.
Using a new approach, clinical experts and AI Scientists have created an AI that understands structured and unstructured data like a Physician, representing a leap in generative real-world data applications. Preliminary results from research conducted by the University of Pennsylvania School of Medicine show that the new reasoning paradigm is superior to general domain LLMs in accuracy, speed and cost. This builds on previous peer-reviewed research that found pairing deep learning with symbolic AI — a set of techniques common in logic, mathematics and computer science — outperforms general domain LLMs in the interpretation of medical variables from electronic medical records.
Register for this webinar today to gain insights into how pairing deep learning with symbolic AI can outperform general domain LLMs for generative real-world data applications.
Keywords: Patient Journey, RWD, Other Software, Commercialization/HEOR/Market Access, Data Science, RWE, AI, Artificial Intelligence, Data Management, Patient Data, HEOR, Clinical Data, Real-World Evidence, Data Analytics, Real-World Data, Electronic Medical Records, Clinical Research
Using a new approach, clinical experts and AI Scientists have created an AI that understands structured and unstructured data like a Physician, representing a leap in generative real-world data applications. Preliminary results from research conducted by the University of Pennsylvania School of Medicine show that the new reasoning paradigm is superior to general domain LLMs in accuracy, speed and cost. This builds on previous peer-reviewed research that found pairing deep learning with symbolic AI — a set of techniques common in logic, mathematics and computer science — outperforms general domain LLMs in the interpretation of medical variables from electronic medical records.
Register for this webinar today to gain insights into how pairing deep learning with symbolic AI can outperform general domain LLMs for generative real-world data applications.
Keywords: Patient Journey, RWD, Other Software, Commercialization/HEOR/Market Access, Data Science, RWE, AI, Artificial Intelligence, Data Management, Patient Data, HEOR, Clinical Data, Real-World Evidence, Data Analytics, Real-World Data, Electronic Medical Records, Clinical Research
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Last modified: 2024-04-13 03:25:04