Skip to content

EchoGo Heart Failure reclassified most cases that scores left open

Singapore's ACE found that EchoGo Heart Failure appeared safe and accurate on retrospective data. It reclassified 73.5% of cases left indeterminate by the HFA-PEFF score.

  • Not rated an organization

    ACE relied on retrospective studies in which the software guided no care, and it found limited data on clinical utility.

Depth runs from 1, a convenience or time saved, to 5, a life or a livelihood preserved.

Status
Partly reported benefit.
Evidence

found, the grade of this recordstudiedreportedclaimed

An independent assessment report supports the benefit.

Compared with

The HFA-PEFF and H2FPEF clinical scores in the main training and validation study. Measured.

Without the system
54.6% and 60.4% non-diagnostic outcomes
With it
7.3% non-diagnostic outputs
The system’s part
The main study set the software's results against two clinical scores, and its authors compared management decisions with and without the model. All the studies were retrospective, and most had funding or authors from Ultromics. ACE describes the software as a machine learning-based decision support system.
Not yet checked
LimitsCosts and harmsLearns from dataLater outcome
Benefit type
Improved Task Accuracy
System
EchoGo Heart Failure
Made by
Ultromics Ltd.
Used by
Hospitals in the retrospective US and UK studies that ACE reviewed (not yet in use in Singapore)
Where
United States and United Kingdom (studies), assessed for Singapore
Stage
Tested in a laboratory
Date
, when the source was published
Kind
Aggregate result
Broad benefit
Identifying Objects, Actions, and Events, Analyzing Data or Information
Collections
Scrutiny and findings, Cross-border records
Last revised
1 November 2026

Sources

  1. Assessment report, by authors with no tie to the system.

    Agency for Care Effectiveness (ACE), Ministry of Health, Singapore. EchoGo Heart Failure to Aid in the Diagnosis of Heart Failure with Preserved Ejection Fraction. ACE Brief for New and Emerging Health Technologies, HSB-M 01/2025, dated March 2025, published on 30 April 2025. Summary of Key Points, p. 2.

    Based on three retrospective case-control studies (one of which is a conference abstract) and one retrospective real-world study, EchoGo Heart Failure appeared to be safe and accurate, with limited clinical utility data.
    Although it appears to be less accurate than traditional clinical scores, it can reclassify indeterminate cases resulting from them.

Details

AI system

Workflow

The software read one apical four-chamber video clip from a routine transthoracic echocardiogram showing an ejection fraction of at least 50%. It sent a binary HFpEF classification to the physician's workstation through a cloud server within 20 minutes.

Follow-up

Conditions for replication

Patients are adults over 25 years suspected of heart failure, with an ejection fraction of at least 50%. An interpreting clinician uses the result as an adjunct to standard diagnostic pathways. Cloud processing of patient data must meet data protection rules, such as Singapore's Personal Data Protection Act.

Entry details

Sector

Healthcare.

Purpose

Ultromics built EchoGo Heart Failure to help clinicians detect heart failure with preserved ejection fraction from a single routine echocardiogram clip.

30 more questions not yet checked

model, release, provider, role, configuration, inputs and outputs, autonomy, human oversight, beneficiaries, reach, distribution and access, duration, every measurement question, every money question, ownership and control, dependencies, cross-border connections, geopolitical implications, replication attempts, availability, institutional decision, grounds, action and result, success criterion, every evidence question, observed or intended, alternative assessments, related entries, other identifiers, category mappings.

Cite this record

Peter H. Vartanian. (2026). EchoGo Heart Failure reclassified most cases that scores left open (AIBD-1162). Artificial Intelligence Benefits Database, edition of 1 November 2026. https://petervartanian.xyz/aibd/records/AIBD-1162.html (archived at https://doi.org/10.7910/DVN/AADSII, version 7.0)

BibTeX Data Field definitions