Update README.md

README.md

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 ---
 license: bsd-3-clause
+library_name: scikit-learn
+pipeline_tag: tabular-regression
+tags:
+- MRI
+- medical-imaging
+- ZAP
+- random-forest
+- regression
 ---
+
+# Liver ZAP Random Forest Regression Models
+
+This repository contains trained random forest regression models for
+accelerated liver Z-spectrum analysis proton (ZAP) parameter estimation.
+
+The release includes models for two acquisition configurations:
+
+- 12 frequency offsets for greater acquisition acceleration
+- 20 frequency offsets for improved quantitative agreement
+
+Each configuration estimates:
+
+- relatively free fraction, \(F_f\)
+- apparent transverse exchange time, \(T_{2,f}^{\mathrm{ex}}\)
+- apparent transverse exchange time, \(T_{2,r}^{\mathrm{ex}}\)
+
+## Files
+
+`liver_zap_rfr_models_v1.zip` contains the trained scikit-learn models,
+selected frequency offsets, model manifest, software environment, release
+notes, license, and integrity checksums.
+
+## Source code
+
+https://github.com/vmalis/ZAP-RFR
+
+## Intended use
+
+These models support research evaluation of accelerated liver ZAP imaging.
+They are not medical devices and are not intended for diagnosis or treatment
+decisions. Application to different scanners, acquisition protocols, tissues,
+or populations requires independent validation.
+
+## Security
+
+The models use Python `joblib` serialization and therefore have Python pickle
+semantics. Load model files only from trusted sources and verify their
+SHA-256 checksums before use.