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Artificial Intelligence Guided Echocardiographic Screening of Rare Diseases (EchoNet-Screening)

Artificial Intelligence Guided Echocardiographic Screening of Rare Diseases

Who can join

Ages 18 and older · All sexes

Inclusion Criteria:

* Patients who have a high suspicion for cardiac amyloidosis by AI algorithm

Exclusion Criteria:

* Patients who decline to be seen at specialty clinic
* Patients who have passed away

About the study

Despite rapidly advancing developments in targeted therapeutics and genetic sequencing, persistent limits in the accuracy and throughput of clinical phenotyping has led to a widening gap between the potential and the actual benefits realized by precision medicine.

Recent advances in machine learning and image processing techniques have shown that machine learning models can identify features unrecognized by human experts and more precisely/accurately assess common measurements made in clinical practice.

The investigators have developed an algorithm, termed EchoNet-LVH, to identify cardiac hypertrophy and identify patients who would benefit from additional screening for cardiac amyloidosis and will prospectively evaluate its accuracy in identifying patients whom would benefit from additional screening for cardiac amyloidosis.

What is being tested

• EchoNet-LVH screening for cardiac amyloidosis (other)

Sponsor: Cedars-Sinai Medical Center · Participants: 300 · Started: Nov 18, 2021

Contact the study team

Official record on ClinicalTrials.gov — NCT05139797

Locations in the U.S.

Conditions

• Familial Amyloid Neuropathies

From ClinicalTrials.gov, data retrieved Oct 1, 2026. Each study sets its own eligibility; the study team decides who can join.