Transparent Machine Learning Model to Understand Drug Permeability through the Blood–Brain Barrier
Hengjian Jia, Gabriele C. Sosso · 2024
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Description
Hengjian Jia and Gabriele Sosso present a 2024 learning model that predicts whether a drug can cross the blood-brain barrier, in a form users can read. Top past models hit high accuracy but hide their rules in mixed, opaque traits. That black-box wall blocks design rules for the next drugs.
Their model uses a plain, clear trait set and still matches top accuracy. A simple Bayes tool then mines the results for which traits push a drug through or hold it back. The work aims to turn raw prediction into rules chemists can use.
Catalog record
| CREATOR | Hengjian Jia, Gabriele C. Sosso |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 46 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |