Page 143 - AI for Good-Innovate for Impact - An Interim Report 2024
P. 143

AI for Good-Innovate for Impact



               •    Completed in the second half of 2024: pre consultation health assessment, medical
                    research assistant scientific research data analysis and statistics, paper analysis, assisted
                    paper writing, automatic output of general inspection reports, drug inquiry, drug
                    knowledge Q&A, medication guidelines, personalized follow-up, health assessment and
                    other services. Further promote the application scope                                           32-ChinaUnicom

               In the future, we will further iterate our product capabilities based on market and medical
               patient needs, and promote them to more hospitals.


               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

               •    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.

































                                                                                                    129
   138   139   140   141   142   143   144   145   146   147   148