NCBI PubMed Central
open access
Predicting Long-Term Depression Progression in Parkinson's Disease: A Machine-Learning Survival Analysis and Risk Score.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Development and validation of a multimodal nomogram predicting anxiety and depression in Parkinson's disease: integrating plasma biomarkers and clinical phenotypes.#465187
- Dataset supporting a study of cognition, emotion regulation, and mental health in Parkinson’s Disease#339291
- Surveying Concerns about the Future in People with Parkinsons Disease#651101
- Prediction of depressive symptoms in middle-aged and older adult hospitalized patients with chronic diseases: a multicenter study in Anhui, China using machine learning methods.#399606
- Clinical progression in alpha-synuclein positive LRRK2-PD and sporadic Parkinsons disease: a longitudinal analysis#29783
Record · ID 156939
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive