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Whether it’s heart rate tracking or a reminder to take medicine, the Internet of Things (IoT) has brought a new revolution in the healthcare industry. IoT is bridging the gap between doctors, healthcare facilities and patients by allowing them to connect remotely.

Grand View Research revealed that the global IoT in the healthcare market is expected to reach $534.3 billion by 2025, expanding at a CAGR of 19.9% over the forecast period. From personal fitness tracking products to remote monitoring applications and surgical robots, IoT has the potential to bring innovation to the healthcare ecosystem.

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The Coronavirus is hitting hard on the world’s economy, creating a high volume of uncertainty within organizations. Cybersecurity firm Cynet today revealed new data, showing that the Coronavirus now has a significant impact on information security and that the crisis is actively exploited by threat actors. In light of these insights, Cynet has also shared a few ways to best prepare for the
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AI Transformation in Medical Diagnoses

Within every aspect of healthcare, time is considered the most valuable component. Even minutes of delay can result in the loss of life. Early diagnosis lies at the heart of healing patients, and timely execution of treatment is of primary importance. At an average, doctors spend 15 minutes with each patient, which when considered intently, is grossly insufficient in providing a comprehensive diagnosis of the illness. In an ideal situation, a diagnosis should be made after careful consideration of all relevant patient information, including similar cases and demographics.

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As the healthcare industry gradually moves toward an AI-driven world, things that were previously considered a hindrance or unlikely are now fairly simple tasks. Over the years, more than 90% of hospitals in the county have moved from paper-based systems to electronic processes. When it comes to medical diagnoses, patients’ records are of primary importance. Risks towards critical illnesses can be caught through predictive analysis, thereby saving lives and costs. Early diagnosis is no longer a distant hope, but an actuality that can be easily accomplished through advanced systems.

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The healthcare industry has generated plenty of data. The new method of data collection, such as sensor-generated data, has helped this industry to find a spot in the top.

What if this data can be used to provide better healthcare services at lower costs and increase patient satisfaction? Yes, you heard it right. It’s actually possible by applying machine learning (ML) techniques in the healthcare industry.

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Photo credit by US Air Force/Steve Pivnick

As software becomes increasingly ubiquitous in all of our lives, the consequences of their inevitable failures grow as well. To the point: When the United States rushed to digitize medical patient records back in 2009, blinded by the glow of a $36 billion government carrot, it inadvertently set off a chain of events that has now, and in some cases forever, impaired countless lives.

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This article is featured in the new DZone Guide to Artificial Intelligence: Automating Decision-Making. Get your free copy for more insightful articles, industry statistics, and more!

Since February of 2018, scientists from Google’s health-tech subsidiary have pioneered innovative ways of creating revolutionary healthcare insights through artificial intelligence prediction algorithms. Based on the back of a patient’s eye scan, their system can make predictions against the patient’s risk of experiencing a severe cardiac incident.


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Artificial intelligence has expanded its footprints into many significant fields giving new opportunities for AI developers to improve the productivity with better efficiency. The healthcare sector is one of them that AI is going to play a vital role to improve the treatment process more autonomously and with better results in terms of disease diagnosis and medical care assistance.

Further, with more improvement in AI applications, the healthcare sector will be getting more equipped facilities to provide better medical treatments at a faster pace. Actually, there are many subfields where AI is used, and if you don’t know what the use of Artificial Intelligence is in healthcare, then below are a few examples where AI is extensively used at ground levels.


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Singapore’s largest healthcare group, SingHealth, has suffered a massive data breach that allowed hackers to snatch personal information on 1.5 million patients who visited SingHealth clinics between May 2015 and July 2018. SingHealth is the largest healthcare group in Singapore with 2 tertiary hospitals, 5 national specialty , and eight polyclinics. According to an advisory released by


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