Triage & Diagnose

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Caso 02
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Medical Device Companies

Deliver accurate triage & diagnosis

For medical device companies, Idoven's AI technology reduce the repetitive and manual workload of physicians to interpret ECGs, by augmenting existing, non-AI electrocardiogram software to accurately triage and prioritise patients in need of care. AI-based algorithms integrate with existing clinical workflows and surface insights to evaluate and action.

Reduce manual, repetitive tasks analysing ECGs

Minimises the data burden on physicians by reducing false positive and false negative cardiac events triggered by existing software

Enhance detection consistency & accuracy

Comprehensively identifies over 80 cardiac patterns, in seconds/minutes, in a standardised and automated manner

No change in workflow

Seamlessly integrates with current EMR and patient management systems, via API or non-API tools, to avoid changes in the clinical workflow

The Challenge

What if we could help cardiologists  and non-cardiologist physicians make accurate diagnoses, with every patient, every time?

Data burden on physicians

Physicians spend a million hours each day, just in Europe, on the repetitive task of interpreting ECGs. This is time not spent on direct patient care.

Long waiting times

An overstretched health system, exacerbated by the COVID-19 pandemic, has resulted in waiting lists of up to 1-4 months to see a cardiologist in Europe.

Underutilized data from wearables

Valuable real-world data is being generated at unprecedented speed and scale through wearables and other biosensors. Yet, existing analytical tools cannot keep up.

Idoven’s solution

For medical device companies

Idoven delivers AI tools that integrate seamlessly into the clinical workflow to help clinicians triage cardiac events and detect cardiovascular disease earlier.

Surface only clinically relevant insights for care teams to evaluate and action, and reduce false positives and negatives

Get results in “almost real-time” with 30 second ECGs analysed in seconds and 24 hour holters analysed in less than 5 minutes

Seamlessly integrate AI-powered ECG analysis into cardiac monitoring platforms and visualisation tools via API or non-API tools

Case Study

Increasing detection accuracy from Insertable Cardiac Monitors

Partner

Global medical device company

Challenge

Insertable cardiac monitors (ICMs) trigger cardiac events that need to be analysed by cardiologists. However, only a small fraction of these transmissions actually require attention or intervention. Physicians are frustrated by and are unable to manage the excessive data burden.

Solution

Idoven applied its AI algorithms a dataset of heart patients of over two years and demonstrated a reduction in false positive detections by 98%, with a sensitivity of 97% and specificity of 95%. By more effectively triaging events and identifying high-risk patients that require cardiologist attention, our software reduced the data burden on physicians.
Medical Device Companies

Deliver accurate triage & diagnosis

For medical device companies, Idoven's AI technology reduce the repetitive and manual workload of physicians to interpret ECGs, by augmenting existing, non-AI electrocardiogram software to accurately triage and prioritise patients in need of care. AI-based algorithms integrate with existing clinical workflows and surface insights to evaluate and action.

Reduce manual, repetitive tasks analysing ECGs

Minimises the data burden on physicians by reducing false positive and false negative cardiac events triggered by existing software

Enhance detection consistency & accuracy

Comprehensively identifies over 80 cardiac patterns, in seconds/minutes, in a standardised and automated manner

No change in workflow

Seamlessly integrates with current EMR and patient management systems, via API or non-API tools, to avoid changes in the clinical workflow

The Challenge

What if we could help cardiologists  and non-cardiologist physicians make accurate diagnoses, with every patient, every time?

Data burden on physicians

Physicians spend a million hours each day, just in Europe, on the repetitive task of interpreting ECGs. This is time not spent on direct patient care.

Long waiting times

An overstretched health system, exacerbated by the COVID-19 pandemic, has resulted in waiting lists of up to 1-4 months to see a cardiologist in Europe.

Underutilized data from wearables

Valuable real-world data is being generated at unprecedented speed and scale through wearables and other biosensors. Yet, existing analytical tools cannot keep up.

Idoven’s solution

For medical device companies

Idoven delivers AI tools that integrate seamlessly into the clinical workflow to help clinicians triage cardiac events and detect cardiovascular disease earlier.

Surface only clinically relevant insights for care teams to evaluate and action, and reduce false positives and negatives

Get results in “almost real-time” with 30 second ECGs analysed in seconds and 24 hour holters analysed in less than 5 minutes

Seamlessly integrate AI-powered ECG analysis into cardiac monitoring platforms and visualisation tools via API or non-API tools

Case Study

Increasing detection accuracy from Insertable Cardiac Monitors

Partner

Global medical device company

Challenge

Insertable cardiac monitors (ICMs) trigger cardiac events that need to be analysed by cardiologists. However, only a small fraction of these transmissions actually require attention or intervention. Physicians are frustrated by and are unable to manage the excessive data burden.

Solution

Idoven applied its AI algorithms a dataset of heart patients of over two years and demonstrated a reduction in false positive detections by 98%, with a sensitivity of 97% and specificity of 95%. By more effectively triaging events and identifying high-risk patients that require cardiologist attention, our software reduced the data burden on physicians.
Medical Device Companies

Deliver accurate triage & diagnosis

For medical device companies, Idoven's AI technology reduce the repetitive and manual workload of physicians to interpret ECGs, by augmenting existing, non-AI electrocardiogram software to accurately triage and prioritise patients in need of care. AI-based algorithms integrate with existing clinical workflows and surface insights to evaluate and action.

Reduce manual, repetitive tasks analysing ECGs

Minimises the data burden on physicians by reducing false positive and false negative cardiac events triggered by existing software

Enhance detection consistency & accuracy

Comprehensively identifies over 80 cardiac patterns, in seconds/minutes, in a standardised and automated manner

No change in workflow

Seamlessly integrates with current EMR and patient management systems, via API or non-API tools, to avoid changes in the clinical workflow

The Challenge

What if we could help cardiologists  and non-cardiologist physicians make accurate diagnoses, with every patient, every time?

Data burden on physicians

Physicians spend a million hours each day, just in Europe, on the repetitive task of interpreting ECGs. This is time not spent on direct patient care.

Long waiting times

An overstretched health system, exacerbated by the COVID-19 pandemic, has resulted in waiting lists of up to 1-4 months to see a cardiologist in Europe.

Underutilized data from wearables

Valuable real-world data is being generated at unprecedented speed and scale through wearables and other biosensors. Yet, existing analytical tools cannot keep up.

Idoven’s solution

For medical device companies

Idoven delivers AI tools that integrate seamlessly into the clinical workflow to help clinicians triage cardiac events and detect cardiovascular disease earlier.

Surface only clinically relevant insights for care teams to evaluate and action, and reduce false positives and negatives

Get results in “almost real-time” with 30 second ECGs analysed in seconds and 24 hour holters analysed in less than 5 minutes

Seamlessly integrate AI-powered ECG analysis into cardiac monitoring platforms and visualisation tools via API or non-API tools

Case Study

Increasing detection accuracy from Insertable Cardiac Monitors

Partner

Global medical device company

Challenge

Insertable cardiac monitors (ICMs) trigger cardiac events that need to be analysed by cardiologists. However, only a small fraction of these transmissions actually require attention or intervention. Physicians are frustrated by and are unable to manage the excessive data burden.

Solution

Idoven applied its AI algorithms a dataset of heart patients of over two years and demonstrated a reduction in false positive detections by 98%, with a sensitivity of 97% and specificity of 95%. By more effectively triaging events and identifying high-risk patients that require cardiologist attention, our software reduced the data burden on physicians.
Medical Device Companies

Deliver accurate triage & diagnosis

For medical device companies, Idoven's AI technology reduces the repetitive and manual workload of physicians to interpret ECGs, by augmenting existing, non-AI electrocardiogram software to accurately triage and prioritise patients in need of care. AI-based algorithms integrate with existing clinical workflows and surface insights to evaluate and action.

Reduce manual, repetitive tasks analysing ECGs

Minimises the data burden on physicians by reducing false positive and false negative cardiac events triggered by existing software

Enhance detection consistency & accuracy

Comprehensively identifies over 80 cardiac patterns, in seconds/minutes, in a standardised and automated manner

No change in workflow

Seamlessly integrates with current EMR and patient management systems, via API or non-API tools, to avoid changes in the clinical workflow

The Challenge

What if we could help cardiologists  and non-cardiologist physicians make accurate diagnoses, with every patient, every time?

Data burden on physicians

Physicians spend a million hours each day, just in Europe, on the repetitive task of interpreting ECGs. This is time not spent on direct patient care.

Long waiting times

An overstretched health system, exacerbated by the COVID-19 pandemic, has resulted in waiting lists of up to 1-4 months to see a cardiologist in Europe.

Underutilized data from wearables

Valuable real-world data is being generated at unprecedented speed and scale through wearables and other biosensors. Yet, existing analytical tools cannot keep up.

Idoven’s solution

For medical device companies

Idoven delivers AI tools that integrate seamlessly into the clinical workflow to help clinicians triage cardiac events and detect cardiovascular disease earlier.

Surface only clinically relevant insights for care teams to evaluate and action, and reduce false positives and negatives

Get results in “almost real-time” with 30 second ECGs analysed in seconds and 24 hour holters analysed in less than 5 minutes

Seamlessly integrate AI-powered ECG analysis into cardiac monitoring platforms and visualisation tools via API or non-API tools

Case Study

Increasing detection accuracy from Insertable Cardiac Monitors

Partner

Global medical device company

Challenge

Insertable cardiac monitors (ICMs) trigger cardiac events that need to be analysed by cardiologists. However, only a small fraction of these transmissions actually require attention or intervention. Physicians are frustrated by and are unable to manage the excessive data burden.

Solution

Idoven applied its AI algorithms a dataset of heart patients of over two years and demonstrated a reduction in false positive detections by 98%, with a sensitivity of 97% and specificity of 95%. By more effectively triaging events and identifying high-risk patients that require cardiologist attention, our software reduced the data burden on physicians.

Partner with Idoven

Medical device companies

Leverage our AI algorithms to deliver enhanced triage and detection capabilities, at the fraction of the time.

Pharmaceutical companies

Collaborate with our data scientists and cardiologists to develop ECG-based disease biomarkers and monitor drug cardiotoxicities at scale.