PreemptiveAI Clinical SDK

by Measure Labs, Inc. (Dba Preemptiveai, Inc.)  · Based in United States → — The foundation beneath healthcare.
Cardiology Family Medicine Internal Medicine
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Regulatory Status Disclosed

Overview

PreemptiveAI Clinical SDK is a clinical software development kit that utilizes AI to model and predict cardiovascular health metrics. The company aims to transform healthcare from a reactive to a proactive system by providing an early signal that allows primary care to act before symptoms become emergencies. The SDK leverages advanced signal processing and machine learning to interpret biomedical signals from smartphones and wearable devices, offering insights into human physiology for real-time health diagnosis and prediction.

PreemptiveAI’s technology is designed to learn an individual’s physiological baseline and detect meaningful changes long before symptoms appear, using ubiquitous, noninvasive data. The platform has applications in clinical care optimization, population health management, and accelerated drug development.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Predictive Health Monitoring: Uses biomedical signals from smartphones and wearables to forecast health risks like hospital readmissions.
  • Personalized Care: Tailors health plans based on unique patient data.
  • Disease Prevention: Flags potential health issues before symptoms appear.
  • Real-Time Insights: Works seamlessly with wearables and phones to provide continuous monitoring.
  • AI-Powered Precision: Built by AI and medical experts for accuracy in physiological modeling.
  • Longitudinal Learning: Models learn patterns over months and years to distinguish normal fluctuations from meaningful physiological drift.
  • Human Amplification: AI filters noise, allowing clinical teams to focus on meaningful signals and provide targeted interventions.
  • Early Detection: Aims to detect heart disease years before symptoms appear.
  • SDK for integration: Designed as an SDK for integration into third-party mobile applications.

Use Cases

  • Hospitals: Reduces readmissions by predicting which patients need extra care.
  • Doctors: Provides personalized treatment plans to keep patients healthier.
  • Pharma Companies: Speeds up drug design for targeted therapies.
  • Insurance Providers: Matches resources to patient needs efficiently.
  • Remote patient monitoring and identification of health risks.
  • Early detection of cardiovascular disease.

What Physicians Need to Know

ECG/EKG Analysis Capability
The PreemptiveAI Clinical SDK has received FDA 510(k) clearance as a Class II medical device, validating its core physiological modeling technology for clinical-grade monitoring. It leverages advanced signal processing and machine learning to interpret biomedical signals, including photoplethysmography (PPG) signals from smartphones and wearable devices. The SDK is being assessed for its accuracy in measuring heart rate in adults compared to FDA-approved ground truth devices, utilizing ECG and pulse oximeter data. The platform can convert images of ECGs from any format or manufacturer into fully digital waveforms, then run AI algorithms to detect up to 38 different cardiac abnormalities, including basic rhythm analysis, arrhythmias, infarctions, and heart blocks.
Arrhythmia Detection Accuracy
While specific accuracy for the PreemptiveAI Clinical SDK is under evaluation for heart rate measurement, AI-powered ECG systems in general have demonstrated high diagnostic performance for arrhythmia detection. Pooled sensitivity and specificity for AI-based arrhythmia detection across multiple studies were 94.0% and 98.7%, respectively, with an AUC of 0.982. For atrial fibrillation (AF) detection, AI models showed a sensitivity of 92.6% and a specificity of 99.1%. One study on insertable cardiac monitors (ICMs) showed an AI algorithm achieved 95.4% overall accuracy for arrhythmia classification, with 97.19% sensitivity and 94.52% specificity.
Heart Failure Risk Prediction
PreemptiveAI aims to predict health outcomes in real-time using data from smartphones and wearables, identifying risk signals for events like hospital readmissions. In a retrospective study, Preemptive's physiological modeling identified risk signals 72 hours prior to readmission events with 84.7% AUC. The platform's foundation model is designed to predict diseases before they manifest, enabling personalized interventions. AI tools are being developed to predict heart failure years in advance, utilizing genetic and clinical data, and even routine cardiac CT scans to identify subtle changes in fat around the heart. One deep learning model can predict if a patient's heart failure condition will worsen within a year, specifically if the ejection fraction will fall below 40%.
Cardiac Monitoring Integration
PreemptiveAI leverages biomedical signals from smartphones and wearable devices to create a continuous, normalized data stream for real-time health prediction. The SDK is designed to transform ubiquitous, non-invasive data from consumer devices into personalized, longitudinal insights, learning each individual's baseline and detecting meaningful changes before symptoms appear. This includes the ability to capture rich blood-flow signals from everyday phones and wearables.
Real-Time Alert Capability
PreemptiveAI's platform provides real-time health insights and aims to flag potential issues before symptoms appear. The system is designed to provide early signals to allow primary care to act before symptoms become emergencies. Predictive health platforms, in general, identify patients at high risk of deterioration before physiological signs become clinically apparent, allowing for targeted interventions. These platforms can process dynamic data streams in real-time, providing continuous assessment of a patient's risk profile and triggering alerts for adverse events. AI-powered ECG systems have also been shown to provide rapid and highly accurate detection of arrhythmias and hyperkalemia, facilitating earlier clinical intervention and improving operational efficiency.
Physician Tip

Leverage the PreemptiveAI Clinical SDK for continuous, real-time physiological monitoring from patient smartphones and wearables to gain early insights into potential health risks and facilitate proactive interventions. Utilize the SDK's ECG analysis capabilities to detect a wide range of cardiac abnormalities and support rapid interpretation. Integrate the predictive analytics for heart failure risk to identify at-risk patients earlier and personalize care plans, potentially reducing hospital readmissions. Remember that while AI provides powerful diagnostic support, clinical judgment and confirmatory imaging remain crucial for definitive diagnoses and treatment decisions. The SDK aims to provide a 'missing layer' of continuous physiological data, strengthening existing acute and primary care systems by providing early signals.

The PreemptiveAI Clinical SDK is designed to integrate with existing tools and workflows, leveraging biomedical signals from common smartphones and wearable devices. It aims to provide a continuous, normalized data stream that can be utilized for various applications, including clinical care optimization and population health management. The company is also forming partnerships with healthcare systems and research institutions, such as Duke Health and MultiCare, to enhance its predictive capabilities and support value-based care. The platform's ability to digitize ECGs from various manufacturers and formats suggests broad compatibility with existing ECG devices. Future directions for AI in cardiology involve integrating additional clinical data sources and developing unified platforms to manage outputs from multiple models.

Details

Category Cardiology AI, Clinical Decision Support & Reference, Developer Tools & APIs
Pricing Unknown — unknown
DeploymentSDK for integration into third-party mobile apps (Android/iOS).
Compliance
BAA AvailableUnknown AI-estimated
HIPAA Compliant Yes AI-estimated
FDA Status Cleared AI-estimated

The PreemptiveAI Clinical SDK (K250233) received FDA 510(k) clearance on February 13, 2026, validating its core physiological modeling technology as a Class II medical device. This clearance confirms its substantial equivalence to predicate devices, enabling clinical-grade monitoring at scale.
Integrations
EHR Not specified
Specialties Cardiology, Family Medicine, Internal Medicine

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Press & Coverage

Preemptive Health
Preemptive receives FDA 510(k) clearance
The PreemptiveAI Clinical SDK (K250233) received FDA 510(k) clearance, validating its core physiological modeling technology as a Class II medical device. This clearance confirms the software's substantial equivalence to predicate devices, enabling clinical-grade monitoring at scale.
2026-02
FDA
510(k) Premarket Notification - PreemptiveAI Clinical SDK
This FDA document details the 510(k) Premarket Notification for the PreemptiveAI Clinical SDK, submitted by Measure Labs, Inc. (Dba Preemptiveai, Inc.). The clearance was granted on February 13, 2026, for a Class II medical device.
2026-02
CMI
Cardiac Monitoring Devices Market Size, Trends & Forecast, 2026-2033
This market report highlights that regulatory activity is shifting towards software-enabled cardiac-care ecosystems, with the PreemptiveAI Clinical SDK being among the devices receiving FDA decisions between January and March 2026. This indicates a growing emphasis on algorithm validation and cloud connectivity in the cardiac monitoring market.
2026-08
FDA
TPLC - Total Product Life Cycle - FDA
The FDA's Total Product Life Cycle database lists the PreemptiveAI Clinical SDK (K250233) as substantially equivalent to other devices, with a decision date of February 13, 2026. This entry provides regulatory context for the device's clearance.
2026-07
HealthAIdir
PreemptiveAI Clinical SDK Review & Alternatives - HealthAIdir
HealthAIdir provides a review of the PreemptiveAI Clinical SDK, including links to its official site and regulatory context from the FDA. This resource offers an overview of the product for healthcare AI solutions.
2026-06
Kipra
510(k) - Kipra
Kipra's 510(k) database entry for the PreemptiveAI Clinical SDK (K250233) confirms its clearance on February 13, 2026, by Measure Labs, Inc. This entry provides details on the device's classification and applicant information.
2026-02
Preemptive Health
Preemptive partners with Cove Communities to bring longitudinal care to residents
Preemptive is collaborating with Cove Communities to integrate proactive health monitoring into residential experiences for seniors in Central Florida. This partnership aims to provide longitudinal care directly to residents.
2026-02
Preemptive Health
Duke Health and Preemptive validate early detection model for hospital readmissions
A retrospective study involving 200 patients, conducted by Duke Health and Preemptive, validated an early detection model for hospital readmissions. Preemptive's physiological modeling identified risk signals 72 hours prior to readmission events with 84.7% AUC.
2025-01

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Frequently Asked Questions

The PreemptiveAI Clinical SDK is a software development kit that uses advanced physiological modeling technology to detect subtle changes in a patient's health, aiming for early detection and proactive care. As a physician, you would integrate this SDK into your existing systems to receive early risk signals and longitudinal context, allowing for timely interventions before conditions escalate into emergencies.
Yes, PreemptiveAI, Inc. states that it acts as a business associate to Preemptive Clinic, P.A., handling clinical information in compliance with HIPAA where applicable. They emphasize that their platform's privacy architecture prioritizes data protection, and their application protection supports compliance efforts related to HIPAA by safeguarding sensitive application logic and workflows.
While the PreemptiveAI Clinical SDK strives for clinical-grade accuracy, it's important to remember that no monitoring system is infallible. The insights provided are probabilistic and intended for human review, not as a replacement for clinical judgment. Factors like lighting conditions, device capabilities, and user behavior can impact signal quality, and all clinical decisions remain with human clinicians.
Yes, the market for AI in healthcare is growing rapidly. Alternatives include various AI-powered clinical decision support tools, ambient scribes for documentation, and platforms that offer diagnostic assistance in specialties like radiology and pathology. Examples of other tools include UpToDate Expert AI, OpenEvidence, and numerous AI clinical documentation tools.
Specific pricing for the PreemptiveAI Clinical SDK is not publicly available, as it is often sold to institutions or integrated into existing systems. Generally, pricing for clinical AI tools can vary significantly, with some offering individual subscriptions (e.g., UpToDate Expert AI at $699/year) and others being institution-funded or quote-based. Costs can also include implementation, integration with EHRs, and ongoing service fees.
The PreemptiveAI Clinical SDK has received FDA 510(k) clearance, validating its core physiological modeling technology as a Class II medical device. This clearance confirms its substantial equivalence to predicate devices for clinical-grade monitoring. Additionally, studies, such as one with Duke Health, have validated its early detection model for hospital readmissions, identifying risk signals 72 hours prior to events with 84.7% AUC.
PreemptiveAI is designed to be a supportive layer beneath primary care, providing early signals and context to help clinicians act proactively. The consensus among physicians regarding AI in healthcare is that it should assist, not replace, human clinicians. While AI can streamline tasks and offer insights, clinical expertise, empathy, and ethical judgment remain irreplaceable in patient care, and the SDK's outputs are intended to support, not replace, the physician-patient relationship.

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Suggest an Edit → | Last Verified: 2026-08-19 | First Added: 2026-08-19
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