From sleep apnoea monitoring to algorithm-based diagnostics

From sleep apnoea monitoring to algorithm-based diagnostics

RemoteA aims to play an important role in the future of health care, with its unique algorithm expertise that speeds up diagnosing patients with symptoms of cardio-vascular diseases (CVD). The company has a remarkable knowledge base, having brought innovations to the field of remote diagnostics since 2002.

RemoteA’s first solution utilized a ground-breaking device that made it possible to gather the data needed for diagnosing sleep apnoea at the patient’s home, instead of in the hospital. The company then expanded its business by creating an ECG remote diagnostics platform that was launched in 2005.

“This was a very natural move for us, since CVDs are such serious and common conditions across Europe,” explains RemoteA’s founder and managing director, Ossi Tiihonen. “We wanted to provide a service that would make it easier for GPs to diagnose patients with cardiac symptoms without having to refer them to specialist hospitals for diagnosis.”

Getting more out of algorithms

The year 2007 was a turning point for RemoteA. By then the company had gathered a database of some 5,000 ECG analysis reports through its remote diagnostics platform. This became the foundation for their big-data analysis expertise and related software development. Since then, the amount of available data has significantly grown, making it possible to develop algorithms that become more advanced all the time. Today, the database consists of +1.5 million hours of cardiac data.

RemoteA is constantly striving to get more out of its algorithms. The team is currently finalising the development of SmartECG, an algorithm-based software product supported by EUR 1.2 million of EU funding.

SmartECG will contribute to making health care more effective, as high-quality heart monitoring will become available to more patients than ever before. It will be possible to examine patients faster, more thoroughly and more often than with current methods. In the future, a person suffering from heart problems could connect to the service even before their first appointment with a GP.

“SmartECG is based on our wide experience in providing remote diagnostics services and our deep understanding of algorithms,” says Tiihonen“We seek to further develop our algorithms all the time, as this will make it possible to analyse heart signals even better in the future.”

The company uses an advanced methodology called ‘deep learning’, where advanced machine learning algorithms permit software to learn to perform complex tasks with the help of neural networks and vast amounts of data.

Ossi Tiihonen explains that according to RemoteA’s vision, algorithm-based decision making can help health care widely in the future. “All data on a person’s health will be stored in one place, and artificial intelligence can combine this data in a useful way. Thus, patients needing medical care will receive specialist health care faster, while those with early signs of diseases will receive preventive guidance,” he says.

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