AID — SLICE-3D checkpoints
Checkpoints for AID (Adaptive Importance-guided Discretized Reconstruction), an image + tabular multimodal self-supervised pre-training framework.
Code: https://github.com/Ethan-ysliu/AID
Files
pretrain/aid_slice3d_pretrain_50bins.ckpt pre-training checkpoint
finetune/fold{0..4}_finetune_best.pth fine-tuned classifiers (5 folds)
Usage
huggingface-cli download EthanL06/AID-SLICE3D --local-dir ./ckpts
python run.py test \
--checkpoint ./ckpts/pretrain/aid_slice3d_pretrain_50bins.ckpt \
--model_dir ./ckpts/finetune \
--test_csv <test_ids.csv> \
--metadata_csv <metadata.csv> \
--image_dir <image_dir>
License
Released under CC BY-NC 4.0 — academic research use only, no commercial use.
Data: ISIC 2024 (SLICE-3D); see the ISIC archive for per-image attribution and licensing.
Research use only. Not a medical device.
Citation
@inproceedings{liu2026aid,
title = {Unlocking the Power of Medical Tabular Data via Semantic-Aware Multimodal Pre-training},
author = {Liu, Yingsheng and Li, Haiming and Zhu, Jingmin and Sun, Jiajun and
Mar, Victoria and Janda, Monika and Soyer, H. Peter and Ge, Zongyuan and Yu, Zhen},
booktitle = {Medical Image Computing and Computer Assisted Intervention (MICCAI)},
year = {2026}
}