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The Tyto Insights for Rhonchi Detection is a prescription-use artificial intelligence (AI) enabled decision support software system used in the evaluation of lung sounds in adults and pediatrics (2 years and older). It automatically analyzes the acoustic signal of the lung as recorded by the FDA 510k cleared compatible Tyto Stethoscope and identifies recordings where a specific abnormal lung sound suggestive of "Rhonchi" is suspected. It is not intended to detect other abnormal or normal lung sounds. A licensed health care professional's advice is required to understand the meaning of the Tyto Insights for Rhonchi Detection result. Healthcare providers should consider the device result in conjunction with recording and other relevant patient data.

The Tyto Insights for Rhonchi Detection is a web-based AI-enabled software system designed to aid in the clinical assessment of lungs auscultation sound data by analyzing recorded lung sounds to determine whether a Rhonchi is detected within the recorded sound data. The Tyto Insights for Rhonchi Detection Software is intended to process recordings from the FDA-cleared compatible Tyto Stethoscope (Tyto Stethoscope, K181612). The acquisition of the acoustic data (recordings) is carried out by a professional user in a clinical environment or by a lay- user in a non-medical environment, in compliance with the labeling of the Tyto Stethoscope. The system is composed of the following sub-systems:

1. The Tyto Insights for Rhonchi Detection Application Server (APS) communicates with the Tyto Insights for Rhonchi Detection Algorithm Server (ALS) and implements an application programming interface (API) for communication with the telehealth server.

2. The Tyto Insights for Rhonchi Detection Algorithm Server (ALS) receives an audio file as input and returns an analysis result of positive or negative regarding whether a Rhonchi was detected as output.

3. The Tyto Insights for Rhonchi Detection Web Server (WBS) provides a graphic indication whether a Rhonchi is detected in the recording. It can be utilized both in the patient and clinician side.

All the software subsystems (servers and storage) are hosted in the cloud and communicate through IP network.

The recordings from the compatible Tyto Stethoscope (K181612) are sent by the third-party point of care app to the clinician app through the telehealth server. The telehealth server sends the set of the lung sound recordings to the Tyto Insights for Rhonchi Detection web server using its dedicated API. The AI enabled algorithm runs automatically and returns a response for each audio file with the indication of rhonchi to the telehealth server which sends a response to both the clinician side and the patient side.

Here's a breakdown of the acceptance criteria and study details for the Tyto Insights for Rhonchi Detection, based on the provided FDA 510(k) clearance letter:

Acceptance Criteria and Device Performance

1. Table of Acceptance Criteria and Reported Device Performance

Study Details

2. Sample size used for the test set and the data provenance

• Sample Size: 400 recordings (100 Rhonchi positive and 300 negative) from 400 patients.
• Data Provenance: Retrospective validation dataset composed of recordings obtained from the real-world use of the Tyto Care FDA-cleared compatible Tyto Stethoscope (K181612). The country of origin is not explicitly stated, but Tyto Care Ltd. is based in Israel, suggesting possible international data acquisition or a mix.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Number of Experts: Three.
• Qualifications of Experts: Blinded experienced Pulmonologists. Specific years of experience are not mentioned.

4. Adjudication method for the test set

• Adjudication Method: Majority vote (2+1) of the three blinded Pulmonologists. The binary ground truth was determined if at least two out of the three experts agreed.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

• An MRMC study was performed comparing the device's AUC to that of clinical readers (non-Pulmonologists).
• Effect Size: The difference in AUC (Tyto Insights for Rhonchi Detection – clinical readers) was 0.16 (0.13–0.21). This indicates that the device itself performed better than the clinical readers (non-Pulmonologists) in detecting rhonchi, establishing non-inferiority with a positive margin. The study did not evaluate how much human readers improve with AI assistance (i.e., human-in-the-loop performance), but rather compared standalone AI performance to standalone human reader performance.

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done

• Yes, a standalone performance evaluation was done. Table 3 explicitly provides "The stand-alone accuracy of the Tyto Insights for Rhonchi Detection" with Sensitivity, Specificity, PPV, and NPV.

7. The type of ground truth used

• Type of Ground Truth: Expert consensus. Specifically, a majority vote from three experienced Pulmonologists.

8. The sample size for the training set

• The document does not explicitly state the sample size for the training set. It only mentions the retrospective validation dataset of 400 recordings. The PCCP section mentions "Re-training of the ML model with additional data," which implies a training set was used to develop the initial model, but its size is not provided in this document.

9. How the ground truth for the training set was established

• The document does not explicitly describe how the ground truth for the training set was established. It only details the ground truth establishment method for the validation dataset (majority vote by three pulmonologists). It's reasonable to infer a similar method might have been used for the training data, but it's not stated.

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The TytoCare Lung Sounds Analyzer is an over-the-counter decision support software system used in the evaluation of lung sounds in adults and children (2 years and older). It automatically analyzes the acoustic signal of the lung as recorded by the FDA cleared compatible Tyto Stethoscope and identifies recordings where a specific abnormal lung sound suggestive of "Wheeze" is suspected. It is not intended to detect other abnormal or normal lung sounds. A licensed health care professional's advice is required to understand the meaning of the TytoCare Lung Sounds Analyzer result. Healthcare provider should consider the device result in conjunction with recording and other relevant patient data.

The TytoCare Lung Sounds Analyzer is a web-based software system designed to aid in the clinical assessment of lungs auscultation sound data by analyzing recorded lung sounds to determine whether a Wheeze is detected within the recorded sound data.

The TytoCare Lung Sounds Analyzer Software is intended to process recordings from the FDA-cleared compatible Tyto Stethoscope (Tyto Stethoscope, K181612). The acquisition of the acoustic data (recordings) is carried out by a professional user in a clinical environment or by a lay- user in a non-medical environment, in compliance with the labeling of the Tyto Stethoscope.

The system is composed of the following sub-systems:

• 1. The TytoCare Lung Sounds Analyzer Application Server (APS) communicates with the TytoCare Lung Sounds Analyzer Algorithm Server (ALS) and implements an application programming interface (API) for communication with the telehealth server.
• 2. The TytoCare Lung Sounds Analyzer Algorithm Server (ALS) receives an audio file as input and returns an analysis result of positive or negative regarding whether a wheeze was detected as output.
• 3. The TytoCare Lung Sounds Analyzer Web Server (WBS) provides a graphic indication whether a wheeze is detected in the recording. It can be utilized both in patient and clinician side.

All the software subsystems (servers and storage) are hosted in the cloud and communicate through IP network.

Here's a breakdown of the acceptance criteria and the study details for the TytoCare Lung Sounds Analyzer, based on the provided document:

Acceptance Criteria and Device Performance

Study Details

1. Sample size used for the test set and the data provenance:

   • Sample Size: 371 recordings (86 Wheeze positive, 285 negative) from 359 patients.
   • Data Provenance: Retrospective validation dataset of Tyto Stethoscope recordings sourced from real-world use of the Tyto Care FDA cleared Tyto Stethoscope. The dataset included recordings from patients with known pre-existing conditions (COPD or Asthma) (7.28%).

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Number of Experts: Three.
   • Qualifications: Blinded experienced Pulmonologists. Specific years of experience are not mentioned.

3. Adjudication method for the test set:

   • Adjudication Method: Majority vote of the three blinded Pulmonologists ("binary ground truth was determined by majority vote of these three Pulmonologists"). This is a 3-reader consensus method.

4. If a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was done:

   • Yes, a comparative study was done. The clinical performance section compares the device's AUC to that of "clinical readers (Physicians non-Pulmonologists)."
   • Effect size of how much human readers improve with AI vs. without AI assistance: The study primarily focused on the device's accuracy being non-inferior to human readers, rather than human readers with AI assistance. The reported AUC for the device (0.91) was higher than the AUC for clinical readers (0.83), with a difference of 0.09. This suggests the device performs better than the un-assisted clinical readers. The study did not test human readers with AI assistance, so an effect size for human improvement with AI assistance cannot be determined from this document.

5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:

   • Yes, a standalone accuracy assessment was performed. Table 3 explicitly presents "The stand-alone accuracy of the TytoCare Lung Sounds Analyzer" with sensitivity and specificity results.

6. The type of ground truth used:

   • Type of Ground Truth: Expert consensus. Specifically, a majority vote of three blinded experienced Pulmonologists.

7. The sample size for the training set:

   • The document does not provide the sample size for the training set. It only mentions the validation dataset.

8. How the ground truth for the training set was established:

   • The document does not provide information on how the ground truth for the training set was established. It only describes the ground truth establishment for the validation dataset.

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