AI and LLMs
Developing & implementing AI-based solutions
is a core IPRD capability
IPRD’s team has decades of experience developing computer-vision based solutions for easy-to-use biometric matching, automatic rapid diagnostic test reading, and many other AI-based solutions.
La mission d'IPRD est de fournir un accès à des innovations de santé numérique évolutives avancées qui permettent des solutions de santé mondiale disruptives et percutantes dans les PRITI.
Recent advances in large language models (LLMs) can potentially enable disruptive impact across multiple use cases from health to agriculture in LMICs. IPRD’s extensive experience in research, development, and deployment of advanced AI-based solutions at scale in real-world environments, makes it uniquely positioned to take an LLM use case and turn it into impact.
IPRD’s LLM STRATEGY HAS 3 COMPONENTS: CONTENT, IMPACT and CONTROL
We believe that, since LLMs have largely been trained on information derived primarily from outside LMICs, then our focus on leveraging context-based content, such as WHO Guidelines, local Ministry of Health or Agriculture guidance documents, as well as a patient or other specific record, as examples, will be critical in the effective use of LLMs in LMICs.
LLMs are particularly powerful at summarizing spoken and/or textual content into succinct, actionable steps, for example between a worker and a person in a clinic or community setting.
The approach leverages three collections of information:
The patient record (new and old) as normally entered by a HCW into ImpactHealth
A WHO ANC guideline document
Contextual information on who the participants are in the dialog created by the LLM