Page 145 - AI for Good-Innovate for Impact Final Report 2024

AI for Good-Innovate for Impact

32�3� Use case requirements

ITU-T Supplement Y.71 ITU-T Y.3000 series – Use Cases for AI-Driven Medical Assistance and
Clinical Research Support 32-ChinaUnicom

• YJ-LM-UC32-REQ-001: It is critical that YJ-LM are capable of processing and analyzing
large amounts of data from various sources, contribute to more accurate diagnoses and
treatments, leading to better health outcomes globally.
• YJ-LM-UC32-REQ-002: It is crucial that YJ-LM have a user-friendly interface that allows
both healthcare professionals and patients to easily interact with it, making healthcare
more accessible and reducing health disparities.
• YJ-LM-UC32-REQ-003: It is vital that YJ-LM provide support for medical research, such as
data retrieval and processing services, accelerating medical advancements and leading
to the development of new treatments and therapies.
• YJ-LM-UC32-REQ-004: It is imperative that YJ-LM offer a range of healthcare services,
such as pre-diagnosis information collection, department recommendations, and health
report interpretation, making healthcare more efficient and patient-centric.
• YJ-LM-UC32-REQ-005: It is important that YJ-LM continuously learn and improve based
on feedback and new data, ensuring that the model stays up-to-date and continues to
provide high-quality healthcare services.
• YJ-LM-UC32-REQ-006: It is necessary that YJ-LM adhere to all relevant ethical guidelines
and regulations, particularly those related to data privacy and security, maintaining trust
in AI and its role in healthcare.
• YJ-LM-UC32-REQ-007: It is essential that YJ-LM clearly communicates their limitations.
They must state if they are not capable of handling a new case or one that is uncertain to
the model.

32�4� Sequence diagram

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