| Device |
cardiovascular machine learning-based notification software |
| Definition |
Cardiovascular machine learning-based notification software employs machine learning techniques to suggest the likelihood of a cardiovascular disease or condition for further referral or diagnostic follow-up. The software identifies a single condition based on one or more non-invasive physiological inputs as part of routine medical care. It is intended as the basis for further testing and is not intended to provide diagnostic quality output. It is not intended to identify or detect arrhythmias. |
| Physical State |
consists of one or more non-invasive physiological inputs, a machine-learning based model for disease detection or classification, and an output on the presence or likelihood of a single cardiovascular disease or condition |
| Technical Method |
non-invasive physiological measurement(s) |
| Target Area |
Cardiovascular |
| Regulation Medical Specialty |
Cardiovascular |
| Review Panel |
Cardiovascular |
|---|
| Product Code | QXO |
|---|
| Premarket Review |
Office of Cardiovascular Devices
(OHT2)
Cardiac Electrophysiology, Diagnostics, and Monitoring Devices
(DHT2A)
|
| Submission Type |
510(k)
|
|---|
| Regulation Number |
870.2380
|
|---|
| Device Class |
2
|
| Total Product Life Cycle (TPLC) |
TPLC Product Code Report
|
| GMP Exempt? |
No
|
Summary Malfunction
Reporting |
Ineligible |
| Implanted Device? |
No
|
|---|
| Life-Sustain/Support Device? |
No
|
|---|
| Third Party Review |
Not Third Party Eligible |
