# Pathological Classification on ICBHI 2017 (train val)

Source: [Pathological Classification on ICBHI 2017 (train val)](<https://www.sota2.com/research/sota/pathological-classification-on-icbhi-2017-train-val>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-02-26T05:27:06.712Z

Evaluation of Pathological Classification performance on the training and validation splits of the ICBHI 2017 dataset.

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

| Scope | Recorded value |
| --- | --- |
| Task | Pathological Classification |
| Dataset (including any stated split) | ICBHI 2017 (train val) |
| Metric | Accuracy |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 3 of 3 |
| Coverage | All results currently returned for this benchmark |

Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol.

## Metrics

- [Accuracy](<https://www.sota2.com/research/sota/pathological-classification-on-icbhi-2017-train-val.md?metric=Accuracy>): Higher is better; unit: PERCENT.

- [Specificity](<https://www.sota2.com/research/sota/pathological-classification-on-icbhi-2017-train-val.md?metric=Specificity>): Higher is better; unit: PERCENT.

- [Sensitivity](<https://www.sota2.com/research/sota/pathological-classification-on-icbhi-2017-train-val.md?metric=Sensitivity>): Higher is better; unit: PERCENT.

- [ICBHI Score](<https://www.sota2.com/research/sota/pathological-classification-on-icbhi-2017-train-val.md?metric=ICBHI%20Score>): Higher is better; unit: SCALAR.

## Recorded results

| Method | Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| CNN | 99 | Not recorded | 68fa7f781e209131cea9a3f4 |
| Lightweight CNN | 99 | Not recorded | 68fa7f781e209131cea9a3f4 |
| RNN | 95.67 | Not recorded | 68fa7f781e209131cea9a3f4 |

### CNN

Accuracy: 99. Result ID: 698b93407a967eddb76fb753.

[Reporting paper](<https://www.sota2.com/research/paper/68fa7f781e209131cea9a3f4.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa66141e209131cea0e231.md>)

Recorded evaluation configuration: {"Processing":"Mel-spectrogram- VAE \[42\]"}. This record does not assert independent reproduction.

### Lightweight CNN

Accuracy: 99. Result ID: 698b93407a967eddb76fb754.

[Reporting paper](<https://www.sota2.com/research/paper/68fa7f781e209131cea9a3f4.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa7f781e209131cea9a3f4.md>)

Recorded evaluation configuration: {"Processing":"Hybrid Scalogram (Proposed)"}. This record does not assert independent reproduction.

### RNN

Accuracy: 95.67. Result ID: 698b93407a967eddb76fb752.

[Reporting paper](<https://www.sota2.com/research/paper/68fa7f781e209131cea9a3f4.md>)

Recorded evaluation configuration: {"Processing":"MFCC \[39\]"}. This record does not assert independent reproduction.

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