Interpretable time-series neural turing machine for prognostic prediction of patients with type 2 diabetes in physician-pharmacist collaborative clinics
Proposed ITS-NTM could be used to promote the implementation of physician-pharmacist collaborative clinics, and further prompt the application of artificial intelligence to optimize the allocation of medical resources and improve the quality of care in under-resourced areas.
Authors
- Daxiong Xiang (ORCID: https://orcid.org/0000-0002-4226-6574)
- Wang Xie
- Shuting Huang (ORCID: https://orcid.org/0000-0002-1526-8048)
- Bikui Zhang (ORCID: https://orcid.org/0000-0001-7148-7926)
- Yining Chen (ORCID: https://orcid.org/0000-0002-9501-5293)
- Ping Xu (ORCID: https://orcid.org/0000-0001-8692-0219)
- Shenglan Tan (ORCID: https://orcid.org/0000-0003-0292-7195)
- Lei Chen (ORCID: https://orcid.org/0000-0003-1409-8371)
- Xia Li (ORCID: https://orcid.org/0000-0001-8665-7983)
- Jie Xiao (ORCID: https://orcid.org/0009-0002-2261-5682)
- Haiyan Yuan (ORCID: https://orcid.org/0000-0002-4241-0011)
- Yuhan Tan
- Qing Wang (ORCID: https://orcid.org/0009-0009-1303-9776)
- Bin Chen (ORCID: https://orcid.org/0009-0000-9974-9430)
Institutions
- Central South University (CN)
- Second Xiangya Hospital of Central South University (CN)
Publication Details
- Journal
- International Journal of Medical Informatics
- Published
- 2024-11-29
- DOI
- https://doi.org/10.1016/j.ijmedinf.2024.105737
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.71
Funders
- China Medical Board
- Health Commission of Hunan Province
- Health Commission of Henan Province