{
  "id": "AIBD-0268",
  "title": "Mayo Clinic AI-ECG flags low ejection fraction at 97.88%; 41-year-old treated, EF recovers to 55%",
  "summary": "At Mayo Clinic two ECGs scored 97.88% and 98.67% for reduced ejection fraction in a 41-year-old with no cardiac history; echo confirmed HFrEF, therapy followed, EF 55% at 4 months. Developer-authored.",
  "date_observed": "2021-08-24",
  "date_basis": "unassessed",
  "date_precision": "unassessed",
  "benefit_status": null,
  "source_collection": null,
  "source_entry": null,
  "account": "Harmon, Witt, Friedman and Attia (Cardiovascular Digital Health Journal, 24 August 2021) report a 41-year-old man with class III obesity, sleep apnea, no cardiac history. Two electrocardiograms (ECGs) on Mayo's AI-ECG dashboard gave reduced-ejection-fraction probabilities of 97.88% and 98.67%. Echocardiography next day confirmed reduced function. Guideline-directed therapy for new heart failure with reduced ejection fraction (HFrEF) began. At four months his ejection fraction had risen to 55%, attributed by the authors to therapy, recovery from post-viral sequelae and weight loss. All four authors are at Mayo Clinic, which developed the algorithm and licensed it to Eko and Anumana. Friedman, Attia and other inventors may receive financial benefit. The same group published further cases. Dhawan et al. (PACE, 2024): AI-ECGs predicting left-bundle-branch-block cardiomyopathy six years before presentation. Kenyon et al. (J Pers Med, 2024): AI-ECG prompting an early AL amyloidosis diagnosis. Liu et al. (HeartRhythm Case Reports, 2025): defibrillator decision-making. No source outside Mayo was found for these cases.",
  "category": "benefit created",
  "unexpected": false,
  "purpose": "Screen 12-lead ECGs for a low left-ventricular ejection fraction with a convolutional neural network",
  "system": "Mayo Clinic AI-ECG low-ejection-fraction algorithm (AI-ECG dashboard)",
  "model_version": null,
  "developer": "Mayo Clinic (licensed to Eko and Anumana)",
  "deployer": "Mayo Clinic, Rochester",
  "location": "Rochester, Minnesota, USA",
  "domain": "Health; cardiology",
  "segment": "Adults presenting with unexplained symptoms and an ECG",
  "benefit_type": "Improved Physical Health",
  "taxonomy_note": null,
  "registry_ids": {},
  "ratings": [
    {
      "group": "personal",
      "depth": 3,
      "reason": "New HFrEF identified and treated; ejection fraction 55% at four months."
    },
    {
      "group": "organizational",
      "depth": null,
      "reason": "No organizational outcome reported for this case."
    },
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      "reason": "Single case."
    }
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    "statement": "The AI-ECG probabilities (97.88% and 98.67%) prompted the echocardiogram and treatment, according to the authors. The source is the developer's own case report. The authors disclose that Mayo licensed the technology and that inventors may receive financial benefit. No independent account of the case exists."
  },
  "evidence": [
    {
      "kind": "case report",
      "citation": "Harmon DM, Witt DR, Friedman PA, Attia ZI. Cardiovasc Digit Health J 2(5):282-284 (2021)",
      "title": "Diagnosis and treatment of new heart failure with reduced ejection fraction by the artificial intelligence-enhanced electrocardiogram",
      "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8890344/",
      "date": "2021-08-24",
      "written_by": "makers",
      "quote": "The 2 ECGs evaluated by the AI-ECG algorithm revealed high probabilities of reduced ejection fraction (97.88% and 98.67%)"
    },
    {
      "kind": "case report",
      "citation": "Harmon DM, et al. (2021), disclosures",
      "title": "Diagnosis and treatment of new heart failure with reduced ejection fraction by the artificial intelligence-enhanced electrocardiogram",
      "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8890344/",
      "date": "2021-08-24",
      "written_by": "makers",
      "quote": "Drs Friedman and Attia and other Mayo inventors may also receive financial benefit from this agreement through Mayo Clinic policies."
    },
    {
      "kind": "case report",
      "citation": "Dhawan R, Omer M, Carpenter C, Friedman PA, Liu X. Pacing Clin Electrophysiol (2024)",
      "title": "Successful prediction of left bundle branch block-induced cardiomyopathy and treatment effect by artificial intelligence-enabled electrocardiogram",
      "url": "https://doi.org/10.1111/pace.14980",
      "date": "2024-04-07",
      "written_by": "makers",
      "quote": "Artificial intelligence-enabled ECGs performed 6 years prior to clinical presentation consistently predicted a high probability (up to 91%) of low EF."
    },
    {
      "kind": "case report",
      "citation": "Kenyon CR, Pietri MP, Rosenthal JL, Arsanjani R, Ayoub C. J Pers Med 14(6):559 (2024)",
      "title": "Artificial Intelligence Assists in the Early Identification of Cardiac Amyloidosis",
      "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11205191/",
      "date": "2024-05-24",
      "written_by": "makers",
      "quote": "This facilitated an early diagnosis by the biopsy of AL cardiac amyloidosis and the prompt initiation of targeted therapy."
    },
    {
      "kind": "case report",
      "citation": "Liu X, Friedman P, Cha YM, Deshmukh A, Mulpuru S, Asirvatham S. HeartRhythm Case Rep (2025)",
      "title": "Prospective use of artificial intelligence-enabled electrocardiogram to assist in clinical decision making regarding defibrillator therapy",
      "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12666949/",
      "date": "2025-07-26",
      "written_by": "makers",
      "quote": "Prospective use of artificial intelligence-enabled electrocardiogram to assist in clinical decision making regarding defibrillator therapy"
    },
    {
      "kind": "news report",
      "citation": "MedCity News (3 Apr 2024). Eko Health Gains FDA Clearance For Cardiology Algorithm That Can Detect Heart Failure in 15 Seconds.",
      "title": "Eko Health Gains FDA Clearance For Cardiology Algorithm That Can Detect Heart Failure in 15 Seconds",
      "url": "https://medcitynews.com/2024/04/eko-health-gains-fda-clearance-for-cardiology-algorithm-that-can-detect-heart-failure-in-15-seconds/",
      "date": "2024-04-03",
      "written_by": "independent",
      "quote": null
    }
  ],
  "replication": {
    "produced_by": [
      "Routine 12-lead ECGs scored by the low-EF network",
      "A dashboard that clinicians consult during evaluation",
      "Confirmatory echocardiography and guideline-directed therapy"
    ],
    "must_hold": [
      "The algorithm is deployed in the clinical workflow",
      "Clinicians act on a high probability score"
    ],
    "echoes": [
      {
        "date": "2024-04-07",
        "setting": "Mayo Clinic Rochester: 70-year-old with LBBB-induced cardiomyopathy",
        "model_version": null,
        "outcome": "recurred",
        "source": "https://doi.org/10.1111/pace.14980"
      },
      {
        "date": "2024-05-24",
        "setting": "Mayo Clinic Phoenix: 69-year-old woman, AI-ECG amyloidosis probability prompted biopsy",
        "model_version": "AI-ECG amyloidosis model",
        "outcome": "recurred",
        "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11205191/"
      },
      {
        "date": "2025-07-26",
        "setting": "Mayo Clinic Health System, La Crosse: AI-ECG used in defibrillator decision",
        "model_version": null,
        "outcome": "unknown",
        "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12666949/"
      }
    ]
  },
  "paired_incident": null,
  "headline": "Mayo AI-ECG flags low EF; 41-year-old recovers to 55%",
  "metric": "at four months his ejection fraction had improved to 55%",
  "comparator": {
    "against": "the conventional reading of the same ECGs, which showed only nonspecific abnormalities",
    "before": "The ECG showed sinus tachycardia, premature ventricular complexes with rightward deviation, and a nonspecific T-wave abnormality (echocardiography then showed a left ventricular ejection fraction of 41%)",
    "after": "high probabilities of reduced ejection fraction (97.88% and 98.67%); at a 4-month follow-up visit, the patient had improved left ventricular ejection fraction to 55%",
    "basis": "measured",
    "quote": "The 2 ECGs evaluated by the AI-ECG algorithm revealed high probabilities of reduced ejection fraction (97.88% and 98.67%)",
    "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8890344/"
  },
  "later": {
    "status": "scaled",
    "date": "2024-04-03",
    "note": "The Mayo-developed low-ejection-fraction algorithm, licensed to Eko Health and trained on Mayo's ECG dataset, received FDA clearance in early April 2024 for use with Eko's digital stethoscopes, and Mayo authors continued to publish AI-ECG case reports through 2025.",
    "quote": "Eko Health received FDA clearance this week for a new AI-powered tool that aids in the early detection of low ejection fraction",
    "url": "https://medcitynews.com/2024/04/eko-health-gains-fda-clearance-for-cardiology-algorithm-that-can-detect-heart-failure-in-15-seconds/"
  },
  "value": null,
  "developer_country": "United States",
  "deployer_country": "United States",
  "unrated_because": null,
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      "date": "2026-10-21",
      "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.",
      "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/",
      "editor": "AIBD"
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      "date": "2026-10-21",
      "change": "Added what the benefit is measured against, what happened since from the cited sources.",
      "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8890344/; https://medcitynews.com/2024/04/eko-health-gains-fda-clearance-for-cardiology-algorithm-that-can-detect-heart-failure-in-15-seconds/",
      "editor": "AIBD"
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      "change": "Country of the developer and the deployer added from the organization's own site or a registry.",
      "source": "https://en.wikipedia.org/wiki/Mayo_Clinic; https://en.wikipedia.org/wiki/Mayo_Clinic",
      "editor": "AIBD"
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  "confidence": "reported",
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                "citation": "MedCity News (3 Apr 2024). Eko Health Gains FDA Clearance For Cardiology Algorithm That Can Detect Heart Failure in 15 Seconds.",
                "title": "Eko Health Gains FDA Clearance For Cardiology Algorithm That Can Detect Heart Failure in 15 Seconds",
                "url": "https://medcitynews.com/2024/04/eko-health-gains-fda-clearance-for-cardiology-algorithm-that-can-detect-heart-failure-in-15-seconds/",
                "date": "2024-04-03",
                "written_by": "independent"
              }
            ]
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
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          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "sources[].upstream_sources": {
        "state": "not_assessed",
        "review_state": "not_assessed",
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      },
      "strategic_assessments[]": {
        "state": "not_assessed",
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        "state": "value_present",
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          "kind": "record_fields",
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            "summary": "At Mayo Clinic two ECGs scored 97.88% and 98.67% for reduced ejection fraction in a 41-year-old with no cardiac history; echo confirmed HFrEF, therapy followed, EF 55% at 4 months. Developer-authored.",
            "account": "Harmon, Witt, Friedman and Attia (Cardiovascular Digital Health Journal, 24 August 2021) report a 41-year-old man with class III obesity, sleep apnea, no cardiac history. Two electrocardiograms (ECGs) on Mayo's AI-ECG dashboard gave reduced-ejection-fraction probabilities of 97.88% and 98.67%. Echocardiography next day confirmed reduced function. Guideline-directed therapy for new heart failure with reduced ejection fraction (HFrEF) began. At four months his ejection fraction had risen to 55%, attributed by the authors to therapy, recovery from post-viral sequelae and weight loss. All four authors are at Mayo Clinic, which developed the algorithm and licensed it to Eko and Anumana. Friedman, Attia and other inventors may receive financial benefit. The same group published further cases. Dhawan et al. (PACE, 2024): AI-ECGs predicting left-bundle-branch-block cardiomyopathy six years before presentation. Kenyon et al. (J Pers Med, 2024): AI-ECG prompting an early AL amyloidosis diagnosis. Liu et al. (HeartRhythm Case Reports, 2025): defibrillator decision-making. No source outside Mayo was found for these cases."
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
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          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "systems[].autonomy_permissions": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].component_role": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].deployment_configuration": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].inputs_outputs": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].model_name": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].model_version": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].product_name": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "system": "Mayo Clinic AI-ECG low-ejection-fraction algorithm (AI-ECG dashboard)"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "system"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "systems[].provider": {
        "state": "value_present",
        "value": {
          "kind": "structured",
          "data": {
            "application_developer": "Mayo Clinic (licensed to Eko and Anumana)"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Mapped from the existing case description without a new external source review.",
          "record_fields": [
            "developer"
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          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "taxonomy_crosswalks[]": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "title": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "title": "Mayo Clinic AI-ECG flags low ejection fraction at 97.88%; 41-year-old treated, EF recovers to 55%",
            "headline": "Mayo AI-ECG flags low EF; 41-year-old recovers to 55%"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "title",
            "headline"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "version": {
        "state": "value_present",
        "value": {
          "kind": "identifiers",
          "identifiers": [
            "2c17991dfd346309a798adef81faea306475571f2478c5048ad1a84d8169ae7d"
          ],
          "role": "SHA-256 of normalized original case data"
        },
        "provenance": {
          "kind": "curatorial",
          "basis": "Deterministic content version assigned by the local migration.",
          "record_fields": [],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "complete"
      },
      "workflow": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "account": "Harmon, Witt, Friedman and Attia (Cardiovascular Digital Health Journal, 24 August 2021) report a 41-year-old man with class III obesity, sleep apnea, no cardiac history. Two electrocardiograms (ECGs) on Mayo's AI-ECG dashboard gave reduced-ejection-fraction probabilities of 97.88% and 98.67%. Echocardiography next day confirmed reduced function. Guideline-directed therapy for new heart failure with reduced ejection fraction (HFrEF) began. At four months his ejection fraction had risen to 55%, attributed by the authors to therapy, recovery from post-viral sequelae and weight loss. All four authors are at Mayo Clinic, which developed the algorithm and licensed it to Eko and Anumana. Friedman, Attia and other inventors may receive financial benefit. The same group published further cases. Dhawan et al. (PACE, 2024): AI-ECGs predicting left-bundle-branch-block cardiomyopathy six years before presentation. Kenyon et al. (J Pers Med, 2024): AI-ECG prompting an early AL amyloidosis diagnosis. Liu et al. (HeartRhythm Case Reports, 2025): defibrillator decision-making. No source outside Mayo was found for these cases.",
            "replication": {
              "produced_by": [
                "Routine 12-lead ECGs scored by the low-EF network",
                "A dashboard that clinicians consult during evaluation",
                "Confirmatory echocardiography and guideline-directed therapy"
              ],
              "must_hold": [
                "The algorithm is deployed in the clinical workflow",
                "Clinicians act on a high probability score"
              ],
              "echoes": [
                {
                  "date": "2024-04-07",
                  "setting": "Mayo Clinic Rochester: 70-year-old with LBBB-induced cardiomyopathy",
                  "outcome": "recurred",
                  "source": "https://doi.org/10.1111/pace.14980"
                },
                {
                  "date": "2024-05-24",
                  "setting": "Mayo Clinic Phoenix: 69-year-old woman, AI-ECG amyloidosis probability prompted biopsy",
                  "model_version": "AI-ECG amyloidosis model",
                  "outcome": "recurred",
                  "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11205191/"
                },
                {
                  "date": "2025-07-26",
                  "setting": "Mayo Clinic Health System, La Crosse: AI-ECG used in defibrillator decision",
                  "outcome": "unknown",
                  "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12666949/"
                }
              ]
            }
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "account",
            "replication"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      }
    },
    "summary": {
      "total": 91,
      "addressed": 91,
      "known": 29,
      "reviewed": 0,
      "record_mapped": 29,
      "not_assessed": 62,
      "complete": false,
      "by_state": {
        "value_present": 29,
        "not_reported": 0,
        "unresolved": 0,
        "not_assessed": 62,
        "not_applicable": 0,
        "withheld": 0,
        "source_unavailable": 0
      }
    }
  }
}