Codesota · Models · SSAE + Softmax (Explainable ASD)Academic1 results · 1 benchmarks
Model card

SSAE + Softmax (Explainable ASD).

AcademicclassificationStacked Sparse Autoencoder + Softmax1 current SOTA

Stacked Sparse Autoencoder with softmax classifier trained on fMRI functional connectivity. Head movement filtering (FD > 0.2mm) critical for performance. Published in eClinicalMedicine 2025.

§ 02 · Benchmarks

Every benchmark SSAE + Softmax (Explainable ASD) has a recorded score for.

#BenchmarkArea · TaskMetricValueRankDateSource
01ABIDE IMedical · Disease Classificationaccuracy98.2%#1/242025-09-01source ↗
Rank column shows this model’s position vs all other models scored on the same benchmark + metric (competitors after the slash). #1 in red means current SOTA. Sorted by rank, then newest result.
§ 03 · Strengths by area

Where SSAE + Softmax (Explainable ASD) actually performs.

Medical
1
benchmark
avg rank #1.0 · 1 SOTA
§ 04 · Papers

1 paper with results for SSAE + Softmax (Explainable ASD).

  1. 2025-09-01· 1 result

    Identification of critical brain regions for autism diagnosis from fMRI data using explainable AI: an observational analysis of the ABIDE dataset

§ 05 · Related models

Other Academic models scored on Codesota.

BrainTWT
2 results
Causal fMRI Model
2 results
ChebGAT-GCN
2 results
DNTextSpotter (ResNet-50)
2 results
DNTextSpotter (ViTAEv2-S)
2 results
IAST
2 results
LRANet++
2 results
LSGSpotter
2 results
§ 06 · Sources & freshness

Where these numbers come from.

paper
1
result
1 of 1 rows marked verified.