# Patient-level validation of a foundation-model pipeline for pediatric lung sounds: physician-annotated adventitious events are recognized, disease groups are not reliably predicted

arXiv: https://arxiv.org/abs/2603.15688 · HTML: https://mlsanity.com/paper/2603.15688/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 14 references that are in the map.
- First posted on arXiv 15 Mar 2026.

## Builds on (most cited first, 6 of 6)

- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [LoRA: Low-Rank Adaptation of Large Language Models](https://mlsanity.com/paper/2106.09685/) (2021)
- [Axiomatic Attribution for Deep Networks](https://mlsanity.com/paper/1703.01365/) (2017)
- [Visualizing and Understanding Convolutional Networks](https://mlsanity.com/paper/1311.2901/) (2013)
- [HeAR -- Health Acoustic Representations](https://mlsanity.com/paper/2403.02522/) (2024)
- [An Inception-Residual-Based Architecture with Multi-Objective Loss for Detecting Respiratory Anomalies](https://mlsanity.com/paper/2303.04104/) (2023)

## Abstract (arXiv)

Background: Lung-sound classifiers are usually evaluated on recording- or event-level splits, although each child contributes many recordings. We evaluated a foundation-model pipeline (PulmoVec) with the patient as the unit of partitioning and asked whether disease group can be predicted beyond age and sex. Methods: We analyzed 19693 physician-annotated respiratory events from 736 children in the public SPRSound database. A frozen Health Acoustic Representations (HeAR) encoder with low-rank adapters was trained for screening (normal versus adventitious), sound pattern (normal, crackles, wheeze/rhonchi) and disease group (pneumonia, bronchial disease, normal/other); event probabilities were stacked with age, sex and auscultation site. The primary analysis was nested patient-grouped cross-validation; comparators were the majority class, annotated event duration and demographics. Results: The area under the receiver operating characteristic curve (AUC) was 0.95 (95% CI 0.94 to 0.96) for both screening and sound pattern, against 0.78 and 0.75 for event duration alone; the positive predictive value for adventitious events was 0.72. Disease-group prediction reached an AUC of 0.58 (95% CI 0.54 to 0.62), and its accuracy was below the majority-class rate at event level (0.44 versus 0.62) and at patient level (0.46 versus 0.60). Conclusions: Recognition of physician-annotated adventitious events holds under patient-level validation and is not explained by event duration or demographics, although its positive predictive value would limit unaided use. Prediction of disease group, a clinical diagnosis, from lung-sound events alone was not demonstrated. Lung-sound studies should partition data by patient and report non-acoustic comparators.