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Codesota · Tasks · Disease ClassificationHome/Tasks/Medical/Disease Classification

Disease Classification.

Diagnosing diseases from medical images or data.

9
Datasets
57
Results
accuracy
Canonical metric
§ 02 · Canonical benchmark

The reference dataset.

ABIDE I

1,112 resting-state fMRI datasets from 539 individuals with autism spectrum disorder (ASD) and 573 typically developing controls across 17 international sites. Multi-site neuroimaging data for autism classification and biomarker discovery.

Primary metric: accuracy
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§ 03 · Top 10

Leading models.

Leading models on ABIDE I.

#ModelaccuracyYearSource
SSAE + Softmax (Explainable ASD)98.22025paper ↗
2Plymouth DL Model98.02025paper ↗
3MCBERT93.42025paper ↗
4AE-FCN85.02025paper ↗
5ChebGAT-GCN82.02025paper ↗
6ASDFormer81.22025paper ↗
7ASD-SWNet81.02025paper ↗
8BrainGT78.72025paper ↗
9Multi-Atlas DNN78.12025paper ↗
10GCN78.02025paper ↗

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§ 04 · All datasets

Tracked datasets.

9 datasets tracked for this task.

ABIDE I
CANONICAL
33 results · accuracy
Top: SSAE + Softmax (Explainable ASD) 98.2
CheXpert
7 results · auroc
Top: CheXpert AUC Maximizer 93.0
NIH ChestX-ray14
4 results · auroc
Top: TorchXRayVision 85.8
MIMIC-CXR
3 results · auroc
Top: CheXzero 89.2
RSNA Pneumonia Detection
3 results · map
Top: DenseNet-121 (Chest X-ray) 88.5
ABIDE II
2 results · accuracy
Top: DeepASD 93.0
COVID-19 Image Data Collection
2 results · auroc
Top: DenseNet-121 (Chest X-ray) 94.7
VinDr-CXR
2 results · auroc
Top: RAD-DINO 91.2
PadChest
1 result · auroc
Top: TorchXRayVision 84.6
§ 05 · Related tasks

Other tasks in Medical.

Clinical NLPDrug DiscoveryMedical Image Segmentation
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