diff --git a/README.md b/README.md index 7be5fc7f47d5db027d120b8024982df93db95b74..48d77815c86e5b6454abf9a266acb0e5a72ab4b3 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,172 @@ --- license: mit +tags: + - medical-imaging + - chest-x-ray + - insurance-prediction + - fairness + - bias-detection + - mimic-cxr +datasets: + - mimic-cxr --- + +# Insurance Paper — Pretrained Weights + +Pretrained checkpoints for **"The Unawareness of AI Looking for Health Insurance Type from Normal Chest X-ray Images"**. + +All models were trained on [MIMIC-CXR-JPG v2.0.0](https://physionet.org/content/mimic-cxr-jpg/2.0.0/) with seed=123. + +## Models + +| Model | Architecture | Params | File size | +|-------|-------------|--------|-----------| +| MedMamba | VSSM_DoubleLinear / VSSM_Double_addDemothen2 | ~29M | ~115 MB | +| DenseNet121 | DenseNetWithDoubleLinear / _addDemothen2 | ~8M | ~59 MB | +| Swin Transformer V2 | SwinTDoubleLinear / _addDemothen2 | ~50M | ~218 MB | + +## Repository Structure + +``` +insurance_paper_weights/ +├── exp1-1/ # Patch remove-one — MedMamba +│ ├── patch1.pt ... patch9.pt +│ +├── exp1-2/ # Patch keep/remove — DenseNet + SwinT +│ ├── densenet_keep/ +│ │ └── patch1.pt ... patch9.pt +│ ├── swinTF_keep/ +│ │ └── patch1.pt ... patch9.pt +│ └── swinTF_remove/ +│ └── patch1.pt ... patch9.pt +│ +├── exp3/ # Demographics — MedMamba +│ ├── sex.pt, age.pt, race.pt +│ ├── sexage.pt, sexrace.pt, agerace.pt +│ └── sexagerace.pt +│ +├── exp3-1/ # Demographics — DenseNet +│ └── (same 7 files) +│ +├── exp3-2/ # Demographics — SwinT +│ └── (same 7 files) +│ +├── exp4/ # Frequency filtering — MedMamba +│ ├── highpass/ +│ │ └── 1Hz.pt, 5Hz.pt, ... 400Hz.pt +│ └── lowpass/ +│ └── 1Hz.pt, 5Hz.pt, ... 400Hz.pt +│ +├── exp4-1/ # Frequency filtering — SwinT +│ ├── highpass/ └── lowpass/ +│ +└── exp4-2/ # Frequency filtering — DenseNet + ├── highpass/ └── lowpass/ +``` + +## Checkpoint Table + +> **Note:** Exp0 (baseline full-image) and Exp1 (baseline MIMIC-only DenseNet) weights are **not yet trained** and are not included in this repository. + +| Experiment | Description | Model | Config | # Checkpoints | HF path | Available? | +|------------|-------------|-------|--------|---------------|---------|------------| +| **exp0** | Baseline (full image) | densenet, mamba, swinTF | — | 0 | — | **Not trained** | +| **exp1** | Baseline MIMIC-only | densenet | — | 0 | — | **Not trained** | +| **exp1-1** | Patch remove | MedMamba | 9 patches | 9 | `exp1-1/patch{1-9}.pt` | Yes | +| **exp1-2** | Patch keep — DenseNet | DenseNet | 9 patches | 9 | `exp1-2/densenet_keep/patch{1-9}.pt` | Yes | +| **exp1-2** | Patch keep — SwinT | SwinT | 9 patches | 9 | `exp1-2/swinTF_keep/patch{1-9}.pt` | Yes | +| **exp1-2** | Patch remove — SwinT | SwinT | 9 patches | 9 | `exp1-2/swinTF_remove/patch{1-9}.pt` | Yes | +| **exp3** | Demographics (addDemo) | MedMamba | 7 demo combos | 7 | `exp3/{combo}.pt` | Yes | +| **exp3-1** | Demographics (addDemo) | DenseNet | 7 demo combos | 7 | `exp3-1/{combo}.pt` | Yes | +| **exp3-2** | Demographics (addDemo) | SwinT | 7 demo combos | 7 | `exp3-2/{combo}.pt` | Yes | +| **exp4** | Freq filtering — highpass | MedMamba | 8 frequencies | 8 | `exp4/highpass/{F}Hz.pt` | Yes | +| **exp4** | Freq filtering — lowpass | MedMamba | 8 frequencies | 8 | `exp4/lowpass/{F}Hz.pt` | Yes | +| **exp4-1** | Freq filtering — highpass | SwinT | 8 frequencies | 8 | `exp4-1/highpass/{F}Hz.pt` | Yes | +| **exp4-1** | Freq filtering — lowpass | SwinT | 8 frequencies | 8 | `exp4-1/lowpass/{F}Hz.pt` | Yes | +| **exp4-2** | Freq filtering — highpass | DenseNet | 8 frequencies | 8 | `exp4-2/highpass/{F}Hz.pt` | Yes | +| **exp4-2** | Freq filtering — lowpass | DenseNet | 8 frequencies | 8 | `exp4-2/lowpass/{F}Hz.pt` | Yes | + +**Total: 105 trained checkpoints** (exp0 and exp1 not yet trained). + +- **Demo combos** (exp3): `sex`, `age`, `race`, `sexage`, `sexrace`, `agerace`, `sexagerace` +- **Frequencies** (exp4): 1, 5, 10, 25, 50, 100, 200, 400 Hz +- **Patches** (exp1): 1-9, corresponding to a 3x3 grid on 448x448 images (left-to-right, top-to-bottom) + +## Usage + +### Download all weights + +```bash +git lfs install +git clone https://huggingface.co/InsurancePrediction/insurance_paper_weights +``` + +### Download a single experiment + +```bash +# Using huggingface_hub +from huggingface_hub import snapshot_download +snapshot_download( + repo_id="InsurancePrediction/insurance_paper_weights", + allow_patterns="exp3-1/*", + local_dir="./weights" +) +``` + +### Load a checkpoint + +```python +import torch + +# Base model (exp1, exp4) +from model import DenseNetWithDoubleLinear +model = DenseNetWithDoubleLinear(num_classes=2, dropout_prob=0) +ckpt = torch.load("exp1-2/densenet_keep/patch1.pt", map_location="cpu") +model.load_state_dict(ckpt["model_state_dict"]) + +# Demographics model (exp3) +from MedMamba.MedMamba import VSSM_Double_addDemothen2 +model = VSSM_Double_addDemothen2(num_classes=2, demo_size=5) # e.g. sexage -> 2+3=5 +ckpt = torch.load("exp3/sexage.pt", map_location="cpu") +model.load_state_dict(ckpt["model_state_dict"]) +``` + +### Mapping from HF paths to original training paths + +| HF path | Original path in JAMA_codes | +|---------|---------------------------| +| `exp1-1/patch{N}.pt` | `exp1-1/Rand123/Rand123_patchidx{N}_exp1-1_model_aucbest.pt` | +| `exp1-2/densenet_keep/patch{N}.pt` | `densenet_keep/Rand123/Rand123_patchidx{N}_densenet_keep_model_aucbest.pt` | +| `exp1-2/swinTF_keep/patch{N}.pt` | `swinTF_keep/Rand123/Rand123_patchidx{N}_swinTF_keep_model_aucbest.pt` | +| `exp1-2/swinTF_remove/patch{N}.pt` | `swinTF_remove/Rand123/Rand123_patchidx{N}_swinTF_remove_model_aucbest.pt` | +| `exp3/{combo}.pt` | `{combo}_weights/mamba/sunday/Rand123/Rand123_{combo}_mamba_sunday_model_aucbest.pt` | +| `exp3-1/{combo}.pt` | `{combo}_weights/densenet/sunday/Rand123/Rand123_{combo}_densenet_sunday_model_aucbest.pt` | +| `exp3-2/{combo}.pt` | `{combo}_weights/swin/sunday/Rand123/Rand123_{combo}_swin_sunday_model_aucbest.pt` | +| `exp4/highpass/{F}Hz.pt` | `{F}HighPass_weights/mamba/highpass/Rand123/Rand123_{F}HighPass_mamba_highpass_model_aucbest.pt` | +| `exp4/lowpass/{F}Hz.pt` | `{F}LowPass_weights/mamba/lowpass/Rand123/Rand123_{F}LowPass_mamba_lowpass_model_aucbest.pt` | +| `exp4-1/highpass/{F}Hz.pt` | `{F}HighPass_swin_freq/Rand123/Rand123_{F}HighPass_swin_freq_model_aucbest.pt` | +| `exp4-1/lowpass/{F}Hz.pt` | `{F}LowPass_swin_freq/Rand123/Rand123_{F}LowPass_swin_freq_model_aucbest.pt` | +| `exp4-2/highpass/{F}Hz.pt` | `{F}HighPass_densenet_freq/Rand123/Rand123_{F}HighPass_densenet_freq_model_aucbest.pt` | +| `exp4-2/lowpass/{F}Hz.pt` | `{F}LowPass_densenet_freq/Rand123/Rand123_{F}LowPass_densenet_freq_model_aucbest.pt` | + +## Training Details + +- **Dataset**: MIMIC-CXR-JPG v2.0.0 (normal frontal chest X-rays) +- **Task**: Binary classification — Private vs. Public/Government insurance +- **Image size**: 448 x 448 +- **Seed**: 123 +- **Selection**: Best validation AUC checkpoint + +## Citation + +```bibtex +@inproceedings{chen2025unawareness, + title={The Unawareness of AI Looking for Health Insurance Type from Normal Chest X-ray Images}, + author={Chen, Chi-Yu and others}, + year={2025} +} +``` + +## Code + +[GitHub Repository](https://github.com/TODO) diff --git a/exp1-1/patch1.pt b/exp1-1/patch1.pt new file mode 100644 index 0000000000000000000000000000000000000000..e315141fb82f849d4451727af68f5322d1bf31ab --- /dev/null +++ b/exp1-1/patch1.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e266510728298adec5363cf9fc8a4a83e38b0293b5fd9eb529febf66bc5e3c9e +size 119573714 diff --git a/exp1-1/patch2.pt b/exp1-1/patch2.pt new file mode 100644 index 0000000000000000000000000000000000000000..f411f299bda0e36489d8d537b9367f48eb33906a --- /dev/null +++ b/exp1-1/patch2.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid 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