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Five Tech Trends Impacting the Healthcare Industry



Five Tech Trends Impacting the Healthcare Industry

Global, national, and local healthcare systems have gone through more change in the past few years than almost any other industry.

Technologies that were available but not widely used before the pandemic have been brought to the forefront, accelerating a transformation that will impact the entire health ecosystem.

Virtual office visits, mobile telemedicine, health wearables, remote diagnostics, remote disease management, mRNA drugs, genetic screening, and personalized medicine are just a few of the transformations that are rapidly being deployed now, as well as increasingly in the future.

All living human beings have their own personal health, healthcare needs, diets they should abide by, and even special medications or treatments they must undergo either to improve their quality of life or to sustain it entirely.

Determining each person’s individual health and wellness needs, or recommending lifestyle changes to each individual that specifically suits his or her needs might seem almost impossible, but thanks to some of the transformative Hard Trend technologies growing rapidly this year and beyond, that pipe dream is fast becoming reality.

Five Tech Trends Impacting the Healthcare Industry

Will Technology Be The Downfall of Humanity

  1. The accelerated use of wearables, driven by a growing list of advanced sensors, will increasingly provide a personalized way to monitor and diagnose physical and mental problems, in addition to offering new levels of communication and collaboration capabilities.

Wearables will increasingly be used for personal health tracking applications as 5G and other technologies converge to create new value streams and accelerated growth. Apple, with its smartwatch fitted with an increasing number of health sensors and software, joins Google, Samsung and others in an intensifying battle for market share.

An ever-expanding array of new sensors coupled with intelligent software and applications will drive further innovation and sales in other wearable technology designed to uniquely monitor the health of individuals and other behavioral metrics that play a role in their physical well-being. In some cases, as already demonstrated in Apple Watch commercials, these can be life-saving technologies.

For example, there will be an increase in use of smart patches that attach to the skin to enable remote disease management, diagnostics, and the wireless transfer of general health information to a mobile device. Many of these devices already exist, such as patches that people with diabetes wear to check their blood sugar levels without having to prick their fingers.

  1. Increasing speed and availability of wireless broadband, enabled by satellite mega-constellations and 5G wireless, will dramatically expand personal and business networking on a global level — as well as connecting more things.

Satellite mega-constellations such as OneWeb and Starlink consist of thousands of mass-produced small satellites operating in low Earth orbit combined with a network of ground receivers designed to provide internet service to anywhere on the planet. By providing global broadband access, these systems will give individuals and businesses, large and small, wider access to a vastly expanded global network of people and connected products.

The advantage of this level of connectivity in healthcare, as is represented with 5G, enables the creation of new multibillion-dollar businesses designed to help those aforementioned wearable technologies function even faster than they currently do. This will provide a vital improvement in healthcare, especially as it pertains to emergency response and the need for quick diagnosis when the wearer of health-related technology experiences a medical event.

High connectivity also means it will become easier to connect with medical professionals, or, in the event of a medical emergency, to get immediate help wherever the emergency has taken place. There are several variations of 5G, including high-speed and low-latency, and 5G can be deployed with a public and/or private network, following all HIPAA guidelines.

  1. Rapid growth of genomics, gene editing with CRISPR, mRNA and synthetic biology.

Synthetic biology is a rapidly growing field that combines biotechnology, genetic engineering, molecular engineering and computer science and can be used to design and build engineered biological systems. Applications include processing information, fabricating materials and structures, producing energy, manipulating chemicals and even producing food.

CRISPR is a revolutionary gene editing technology that can be used to create human cellular models of disease and genetically modified organisms to mimic disease and correct genetic mutations, likely leveraged in the future to prevent some conditions from being passed onto a newborn. We all witnessed a breakthrough in mRNA technology, used to create successful COVID vaccines in record time and now being used to fight diseases, such as HIV and cancer.

But the unbelievable amount of research that goes into developing some of these medical and biological breakthroughs was greatly accelerated by advances in AI and other technologies, which can handle much of the calculations and processes involved, and will only open the door to more discovery.

  1. Rapid advances in AI will drive augmented thinking and augmented movement using exoskeleton technologies to new levels of application.

Augmented technologies are designed to increase humans’ physical and cognitive capabilities. Augmented thinking technologies will increasingly provide real-time actionable insights and knowledge drawn from AI-enabled data analytics of large data sets to enhance human thinking and problem-solving. Healthcare professionals will increasingly use this to make more informed decisions and solve problems much faster. 

Humans and AI will increasingly have a symbiotic relationship in which each needs the other for peak performance. Augmented movement technologies enhance physical human functionality. A hearing aid is an example of sensory augmentation; an artificial leg is an appendage augmentation; and a 95-pound nurse in Japan wearing a powered exoskeleton so that she can lift a 200-pound patient into a bed is using a functional augmentation.

This type of technology is also a preventative advancement that will keep individuals out of physical therapy clinics by helping them avoid workplace and personal life injuries in the first place. An example of this is seen with GM workers wearing powered exoskeletons to lessen arm, hand and joint problems while assembling cars. All of our physical parts and systems, including our genes, can be augmented, enhanced, or protected, thanks to accelerating technology-driven Hard Trends that are already rapidly moving forward.

  1. Remote working using virtual meeting software and services will continue and expand, but many will return to the office to increasingly find a new focus on using face-to-face to elevate communication, collaboration, innovation, and sales.

Remote working enabled by virtual meeting software and services has proven itself as a powerful way to leverage human resources within healthcare ecosystems, as well as a new way to both retain and attract talent.

Telemedicine hasn’t just allowed many who need to consult with a doctor or get a medical question answered the ability to do so without leaving their homes; it has now become a way to bring critical elements of a medical practice to communities and remote areas that ordinarily would have had to travel great lengths to see a doctor in person.

This is not to say that going forward, we will only attend doctor’s appointments virtually.  Hybrid use is likely to emerge in the healthcare space, much as it is in the job market, where many employees will combine remote with in-office work.

In accordance with my Anticipatory Leader System, we live in a Both/And world. Thinking exponentially about how we use remote communication services like Zoom, Teams, or Skype, and also the ever-expanding usage of Virtual Reality and the Metaverse as we have come to know it, means there will be room for innovative breakthroughs in all areas of medicine that leverage the technology. With more connected devices and increasing global connectivity, millions more will have full accessibility to healthcare.

Leverage These Trends With an Anticipatory Mindset

WiFi 6 IoT and 5G Connecting the Workforce of the Future

As I have taught over the years, Hard Trends are future certainties that will happen. These five tech trends that are impacting the healthcare industry in a multitude of ways are Hard Trends in and of themselves, transforming both internal and customer/patient-facing industry practices. So how can they be used to your advantage as an independent entrepreneur or an Anticipatory-minded healthcare leader?

In regard to the five tech trends represented in this blog, most, if not all, of them pertain to our connectivity to our personal health and well-being as humans, whether that be through a wearable device or virtual connection with a medical professional anywhere in the world. Likewise, technology acting as our partner in expanding our physical capabilities is another common concept.

Good questions to ask yourself to spur innovative thinking include; What unsolved healthcare problems could now be solved using these technologies? And are there yet-to-emerge problems we could use these technology-driven trends to pre-solve, before they stand in the way of progress?  

Digital transformation in healthcare is still in the early stages, and that represents tremendous opportunities for Anticipatory Leaders!

See the future before it happens, download Daniel Burrus’ Top Technology Hard Trends Shaping 2022:

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How Deep Learning Has Proved to Be Useful for Cyber Security



How Deep Learning Has Proved to Be Useful for Cyber Security

The threat of cyber attacks has recently increased dramatically and traditional measures now appear to be insufficiently competent.

Because of this, deep learning in cyber security is rapidly gaining ground and may hold the key to solving all your cybersecurity issues.

With the advent of technology, there is also an increase in threats to data security and the need to protect an organization’s operations using cybersecurity tools. However, companies are struggling due to most cybersecurity tools being dependent. They rely on signatures or evidence of compromise for the threat detection capabilities of the technologies they use to safeguard their business. Because they are only useful for identifying risks they are already aware of, these technologies are useless against unknown attacks. Here is where deep learning in cyber security can alter the course of events. Deep learning, a branch of machine learning, is excellent at using data analysis to address issues. By subjecting the deep neural network to a vast quantity of data, which no other machine learning in the world can handle, digest, and crunch, we are mimicking the brain and how we operate.


The cyber security industry is facing numerous challenges and deep learning technology might just be its salvation.

Behavior Analysis

An essential deep learning-based security strategy for any firm is tracking and examining user activities and habits. Since it goes beyond security mechanisms and sometimes doesn’t trigger any signals or alerts, it is substantially harder to spot than conventional malevolent behavior against networks. For instance, insider attacks happen when employees utilize their legitimate access for nefarious purposes rather than breaking into the system from the outside, making many cyber protection systems ineffective in the face of such attacks.


One effective defense against these attacks is User and Entity Behavior Analytics (UEBA). After a period of adjustment, it can learn the typical patterns of employee behavior and identify suspicious activity that may be an insider attack, such as accessing the system at odd hours, and then raise alarms.

Detection of Intrusion

Intrusion Detection and Prevention Systems (IDS/IPS) are capable of identifying suspicious network activity, blocking hackers from gaining access, and notifying the user about the same. They are generally characterized by well-known signatures and common attack formats. This is helpful in defending against risks like data leaks.
Previously, ML algorithms handled this operation. However, the system generated several false positives as a result of these algorithms, which made the work of security teams laborious and added to their already excessive exhaustion. By more accurately analyzing the traffic, lowering the number of erroneous alerts, and assisting security teams in differentiating between malicious and lawful network activity, deep learning, convolutional neural networks and recurrent neural networks (RNNs) can be used to develop smarter ID/IP systems.

Dealing with Malware

A signature-based detection technique is used by conventional malware solutions like typical firewalls to find malware. The business maintains a database of known risks, which is regularly updated to include brand-new dangers that have recently emerged. Although this method is effective against basic threats, it fails to counter more sophisticated threats. Deep learning algorithms can identify more complicated threats since they are not dependent on the memory of well-known signatures and typical attack techniques. Instead, they become familiar with the system and can see odd behavior that can be a sign of malware or malicious activity.

Email Monitoring

To stop any form of cybercrime, it is essential to monitor the employees’ official email accounts. For instance, phishing attacks are frequently carried out by sending emails to employees and requesting sensitive information from them. Deep learning and cybersecurity software can be used to prevent these kinds of attacks. Using natural language processing, emails may be checked for any questionable activity. Automation is essential for defending against the enormous amount of risks that businesses must deal with, but ordinary machine learning is too constrained and still needs a lot of tweaking and human involvement to produce the desired outcomes. Deep learning in cyber security goes above and beyond to keep improving and learning over time so that it can foresee hazards and stop them before they materialize.

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