Yuan Ji

Oct 13, 2024 | dev.to | Yuan Ji

After completing my demo project on Keycloak OAuth2 Token Exchange, I decided to expand the idea and created a new demo project called my-ai-doctor. Unlike the previous demo, which focused on backend integration, this project uses Elm for the UI and Docker Compose to run all six servers locally: the Keycloak server, API server, and the SPA web servers for both MyDoctor and MyHealth. The first challenge was building the Elm Land project and deploying it to Docker containers.

Oct 6, 2024 | mdpi.com | Zhe Wu |Yuan Ji |Ke Zhang |Li Jing

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.

Sep 16, 2024 | dev.to | Yuan Ji

After I finished my Oauth 2 Token Exchange demo project, I suddenly had a desire to write the front end UI with Elm language. Elm is my favorite front end language: elegant, functional, strongly typed. But I haven't touched Elm for over a year, so it would take a while to remember how to start. Fortunately, or coincidentally, ChatGPT o1 just came out, and I wanted to see if it is as good as people say.

Mar 14, 2024 | nature.com | Yuan Ji |Qiang Xu

AbstractSchizophrenia is a mental health disorder characterized by functional dysconnectivity. Eigenvector centrality mapping (ECM) has been employed to investigate alterations in functional connectivity in schizophrenia, yet the results lack consistency, and the genetic mechanisms underlying these changes remain unclear. In this study, whole-brain voxel-wise ECM analyses were conducted on resting-state functional magnetic resonance imaging data.

Dec 12, 2023 | nature.com | Yuan Ji

AbstractChronic kidney disease (CKD) is a progressive loss in kidney function. Early detection of patients who will progress to late-stage CKD is of paramount importance for patient care. To address this, we develop a pipeline to process longitudinal electronic heath records (EHRs) and construct recurrent neural network (RNN) models to predict CKD progression from stages II/III to stages IV/V.