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The diagnostic ultrasound system and transducers are intended for diagnostic ultrasound imaging and fluid analysis of the human body.

The clinical applications include: Fetal/Obstetrics, Abdominal, Gynecology, Pediatric, Small Organ, Neonatal Cephalic, Adult Cephalic, Trans-rectal, Muscular-Skeletal (Conventional, Superficial), Urology, Cardiac Adult, Cardiac Pediatric and Peripheral vessel.

It is intended for use by, or by the order of, and under the supervision of, an appropriately trained healthcare professional who is qualified for direct use of medical devices. It can be used in hospitals, clinics and similar care environment for clinical diagnosis of patients.

Modes of Operation: 2D mode, Color Doppler mode, Power Doppler (PD) mode, M mode, Pulsed Wave (PW) Doppler mode, Continuous Wave (CW) Doppler mode, Tissue Doppler Imaging (TDI) mode, Tissue Doppler Wave (TDW) mode, ElastoScan+™ Mode, Combined modes, Multi-Image modes (Dual, Quad), 3D/4D modes.

The HERA W9/ HERA W10 are general purpose, mobile, software controlled, diagnostic ultrasound system. Its function is to acquire ultrasound data and to display the data as B-mode, M-mode, Pulsed wave (PW) Doppler, Continuous wave (CW) Doppler, Color Doppler, Tissue Doppler Imaging (TDI), Tissue Doppler Wave (TDW), Power Amplitude Doppler, Pulse Inversion Harmonic Imaging (S-Harmonic), Directional Power Doppler (S-Flow), Color M-Mode, 3D Imaging Mode, 4D Imaging Mode, Elastoscan+ Mode, Tissue Harmonic Imaging, MV-Flow Mode or as a combination of these modes.

The HERA W9/HERA W10 also give the operator the ability to measure anatomical structures and offers analysis packages that provide information that is used to make a diagnosis by competent health care professionals. The HERA W10 have real time acoustic output display with two basic indices, a mechanical index and a thermal index, which are both automatically displayed.

Here's a summary of the acceptance criteria and the study details for the SAMSUNG MEDISON CO., LTD. HERA W9/HERA W10 Diagnostic Ultrasound System, specifically focusing on the AI-based features mentioned in the document:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not explicitly list quantitative acceptance criteria for the AI-based features. Instead, it states that "Performance testing was successfully completed for the new software functions (artificial intelligence based features HeartAssist, ViewAssist and Slice A) to show passing results for predefined testing criteria," and that for BiometryAssist, "measurement accuracy requirements were met."

Therefore, based on the provided text, the table would look like this:

2. Sample Size Used for the Test Set and Data Provenance

The document does not provide details on:

• The specific sample size used for the test set for any of the AI features.
• The data provenance (e.g., country of origin of the data, retrospective or prospective) for the test set.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications

The document does not provide details on:

• The number of experts used to establish the ground truth for the test set.
• The qualifications of those experts.

4. Adjudication Method for the Test Set

The document does not specify any adjudication method used for the test set. It mentions that clinical studies were not required for substantial equivalence and focuses on performance testing.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

The document does not indicate that an MRMC comparative effectiveness study was done. It focuses on the performance of the AI features themselves rather than comparing human reader performance with and without AI assistance. The text explicitly states: "The subject of this premarket submission, HERA W9/ HERA W10, did not require clinical studies to support substantial equivalence."

6. If a Standalone (algorithm only without human-in-the-loop performance) was done

Yes, the descriptions of HeartAssist, ViewAssist, Slice A, and BiometryAssist (AI version) focus on their automated capabilities ("classification," "proposes caliper placements," "proposes corresponding anatomy annotations," "automatic technology for biometric measurement"). While it mentions user editing, the performance testing appears to validate the algorithm's standalone capabilities against "predefined testing criteria" and "measurement accuracy requirements."

7. The Type of Ground Truth Used

The document states that BiometryAssist's accuracy requirements were met for "biometric measurement," implying that quantitative measurement values (likely manually obtained or from established references) were used as ground truth. For HeartAssist, ViewAssist, and Slice A, the ground truth would likely involve expert-defined "measurement views," "key scanning views," and "anatomy annotations," respectively, but the precise nature (e.g., expert consensus) is not detailed.

8. The Sample Size for the Training Set

The document does not provide details on the sample size used for the training set for any of the AI features.

9. How the Ground Truth for the Training Set was Established

The document does not provide details on how the ground truth for the training set was established. It only generally refers to these features as "deep learning based functions" which implies a training process with labeled data.

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