Artificial Intelligence to Assist in the Treatment of Heart Patients

VTT Technical Research Centre of FinlandThe University of Tampere and TAYS (Tampere University Hospital) Heart Hospital use artificial intelligence (A.I.) technologies developed by VTT Technical Research Centre of Finland in the home care of heart patients. The objective is to recognize serious difficult-to-predict complications as early as possible using the latest methods.

Recently, a clinical study led by Finnish researchers was launched in Tampere to use the latest analytical methods to recognize those myocardial infarction patients at high risk of complications. The project makes comprehensive use of data generated during treatment, but which is usually fragmented into separate systems, and complements it by continuing to monitor how the patient's heart is functioning after he or she has been discharged from hospital. The mass of data thus gathered is analysed using A.I. and machine-learning methods, which have been taught with the help of former patient-treatment data and developed to be applied to myocardial infarction patients.

What the study means for the patients in practice is that a small ECG recorder is attached to their chest when they are leaving the hospital. It can also be linked to the Internet for monitoring purposes for as long as the measurements require.

"The results can be used to enhance patient safety and to target the monitoring more accurately at the patients who would benefit the most from it. In the TAYS area alone, up to a thousand patients a year can benefit from the study," says Kari Antila, Senior Scientist at VTT.

High-risk patients the first group to be monitored
The method that can predict complications, while targeting the monitoring at high-risk patients enables device manufacturers to offer services to professionals and consumers in the international markets.

"High risk patients are identified during treatment, and monitoring is at first targeted at them. In this way, the sensitivity and specificity of the method can be maximised in those situations where the projected probability is high," emphasizes Niku Oksala, Associate Professor of Surgery and the project leader responsible.

"Combining the existing fragmented information into meaningful refined data that supports decision-making is probably the most significant measure for improving cost-efficiency in the context of the current debate concerning Finland's social and health care reform. In addition, it is an important step aimed at enhancing patient safety," says Jussi Hernesniemi, Cardiology Specialist and lead researcher of the project.

The clinical study related to the MADDEC (MAss Data in the Detection and prevention of serious adverse Events leading to complications in Cardiovascular diseases) - project was launched at TAYS Heart Hospital in May, 2017, and the research will be presented at the international EMBEC 2017 conference on 15 June in Tampere.

The project is being implemented as a collaboration between the University of Tampere, VTT, Polytechnic University of Milan (Politecnico di Milano), the TAYS Heart Hospital, and the industrial partners GE Healthcare Finland Oy, Bittium Corporation, Clothing+ Oy and Fimlab Oy. The project is funded by Tekes’ Bits of Health programme, the University of Tampere , VTT, GE Healthcare Finland Oy, Bittium Corporation and Fimlab Oy.

About VTT Technical Research Centre of Finland
VTT Technical Research Centre of Finland Ltd is the leading research and technology company in the Nordic countries. We use our research and knowledge to provide expert services for our domestic and international customers and partners, and for both private and public sectors. We use 4,000,000 hours of brainpower a year to develop new technological solutions.

Most Popular Now

Is Your Marketing Effective for an NHS C…

How can you make sure you get the right message across to an NHS chief information officer, or chief nursing information officer? Replay this webinar with Professor Natasha Phillips, former...

Welcome Evo, Generative AI for the Genom…

Brian Hie runs the Laboratory of Evolutionary Design at Stanford, where he works at the crossroads of artificial intelligence and biology. Not long ago, Hie pondered a provocative question: If...

We could Soon Use AI to Detect Brain Tum…

A new paper in Biology Methods and Protocols, published by Oxford University Press, shows that scientists can train artificial intelligence (AI) models to distinguish brain tumors from healthy tissue. AI...

Telehealth Significantly Boosts Treatmen…

New research reveals a dramatic improvement in diagnosing and curing people living with hepatitis C in rural communities using both telemedicine and support from peers with lived experience in drug...

Research Study Shows the Cost-Effectiven…

Earlier research showed that primary care clinicians using AI-ECG tools identified more unknown cases of a weak heart pump, also called low ejection fraction, than without AI. New study findings...

AI can Predict Study Results Better than…

Large language models, a type of AI that analyses text, can predict the results of proposed neuroscience studies more accurately than human experts, finds a new study led by UCL...

New Guidance for Ensuring AI Safety in C…

As artificial intelligence (AI) becomes more prevalent in health care, organizations and clinicians must take steps to ensure its safe implementation and use in real-world clinical settings, according to an...

Remote Telemedicine Tool Found Highly Ac…

Collecting images of suspicious-looking skin growths and sending them off-site for specialists to analyze is as accurate in identifying skin cancers as having a dermatologist examine them in person, a...

Philips Aims to Advance Cardiac MRI Tech…

Royal Philips (NYSE: PHG, AEX: PHIA) and Mayo Clinic announced a research collaboration aimed at advancing MRI for cardiac applications. Through this investigation, Philips and Mayo Clinic will look to...

New Study Reveals Why Organisations are …

The slow adoption of blockchain technology is partly driven by overhyped promises that often obscure the complex technological, organisational, and environmental challenges, according to research from the University of Surrey...

Deep Learning Model Accurately Diagnoses…

Using just one inhalation lung CT scan, a deep learning model can accurately diagnose and stage chronic obstructive pulmonary disease (COPD), according to a study published today in Radiology: Cardiothoracic...

Shape-Changing Device Helps Visually Imp…

Researchers from Imperial College London, working with the company MakeSense Technology and the charity Bravo Victor, have developed a shape-changing device called Shape that helps people with visual impairment navigate...