| { |
| "approved_by_author": "\u231b", |
| "citation": "Bahado-Singh, R. O., Vishweswaraiah, S., Aydas, B., et al. (2021). Artificial intelligence and leukocyte epigenomics: Evaluation and prediction of late-onset Alzheimer's disease. PLOS ONE, 16(4), e0248375.", |
| "citations": 34, |
| "citations_date": "2026-10-02", |
| "clock_name": "adbahadosingh", |
| "data_type": "DNA methylation", |
| "doi": "https://doi.org/10.1371/journal.pone.0248375", |
| "journal": "PLOS ONE", |
| "last_author": "Uppala Radhakrishna", |
| "model_type": "logistic regression", |
| "n_features": 4, |
| "notes": "PyAging implements the paper\u2019s conventional four-CpG logistic-regression equation and applies a sigmoid to return LOAD case probability; it does not implement the separate high-dimensional deep-learning classifiers also evaluated in the paper.", |
| "platform": [ |
| "Illumina EPIC" |
| ], |
| "population": "older adults", |
| "postprocess": "sigmoid", |
| "predicts": [ |
| "late-onset Alzheimer's disease" |
| ], |
| "research_only": null, |
| "species": "Homo sapiens", |
| "tissue": [ |
| "whole blood" |
| ], |
| "training_target": [ |
| "late-onset Alzheimer's disease" |
| ], |
| "unit": [ |
| "probability" |
| ], |
| "version": "0.5.7", |
| "year": 2021 |
| } |
