All You Need To Know About Healthcare technology is evolving patient care.

Innovative technologies are transforming every field, every industry and healthcare business is no exception. Digital technologies are here to stay in the healthcare market. Like other fields, healthcare industry is also evolving with new technology.

It is estimated that technologies will renovate every small elements of the healthcare including the diagnostics, treatments and how the patient care is delivered in the upcoming years. Although technology has been one of the major force behind inventions in every industry, healthcare sector has been mostly unaffected by technological innovations. As per market research, however this is slowly changing.

New innovative technologies in the healthcare industry

A new era of medication has now begun in which each individual can be clearly defined at singular level instead of on population level. With assistance from the contemporary healthcare technology, we can digitize humans.

That is done by continuous monitoring of each patient’s heat condition, breathing rate, blood pressure, blood oxygen levels & glucose levels, body temperature as well as brain activity and waves etc.

Here are some of the best innovative technologies that have entered the healthcare industry in the recent years. Some of these devices are still underway and are slowly being introduced in the mainstream system.

1.       AI [ Artificial Intelligence]

Artificial intelligence is an advanced form of machine learning, in which software/machines obtain the ability to display or mimic a typical human brain. This can help patient’s outcomes by assisting healthcare practitioners in using medical knowledge, and therefore providing excellent medical/ clinical solutions. According to market research, AI systems will deliver affordable, accessible healthcare to all patients.

2.       Internet of things in Healthcare [IOT]

Internet of things isan increasingly growing technology and has been in discussion in recent years. Healthcare settings can benefit from IOT technology by using real-time site services with devices that can trace patients, medical devices and staff.

3.       Better hospital experience

There are numerous healthcare technology companies that are improving the hospital stays in order to keep updated with the needs of modern patients. This is done by removing wasteful redundancy, enhancing the room design and technological clutter that are in a modern healthcare facility.

According to market research, the new rooms will have adaptable portions that can easily customized as per the specifics of the patient.

4.       3D imaging and improved diagnosis

With technologies like digital image processing design recognition and machine learning. Artificial Intelligence is steadily advancing the procedures and access to trustworthy and accurate image analysis. For example, a startup named Butterfly network has built a small Artificial intelligence powered 3-D ultrasound tool that generates 3D pictures of medical images in real-time. This 3D pictures are sent to cloud services that distinguish the characteristics and automates the diagnosis course. Such applications are expected to have a bigger effect on the overall imaging diagnosis market and its growth.

Conclusion

With extensive improvements in the healthcare technology, the way medical records and data are stored and shared is shifting as well. The enhanced healthcare technology offers more customized treatments, earlier diagnoses, and numerous other benefits for both healthcare professionals and patients.

Why Is The Artificial Intelligence’s contribution in Cyber Security The Most Trending Thing Now?

Cyber- attackers are influencing automation technology at launch strikes, whereas most organizations at rest use physical efforts to collective internal security findings, also putting them in a specific context with outside threat data. With the use of these conventional methods, it can take months or weeks to notice intrusions, during which time invaders can exploit susceptibilities to compromise systems and take out information. To deal with these challenges, ongoing organizations are exploring the use of artificial intelligence (AI) in their day-to-day cyber risk management operations.

According to a technology market report, more than 70% of attacks exploit known vulnerabilities with available patches. Similarly, the findings show that hackers take benefit of vulnerabilities within minutes of their becoming public information. Such statistics emphasize the importance of time-to-remediation. But, because of lack of security professionals and the general challenge of dealing with big data sets in safety, it is not astonishing that vulnerability remediation efforts are not keeping up with cyber challengers. Current industry research proves that it takes organizations on average 146 days to fix critical vulnerabilities.  Noticeably, this benchmark points out you need to rethink existing approach to enterprise security.

Cyber challengers have long influencing machines and automation systems to streamline their operations. Therefore why shouldn’t organizations do the same?

Identification of threats:

Organizations face a rising battle when it comes to cyber security, as the attack surface they have to protect has extended importantly and is predicted to balloon even further. In previous times, it was adequate to focus on endpoint protection and network, however now with applications, cloud services, and mobile devices (e.g., mobile phones, tablets, Bluetooth devices, and smart watches) Organizations are battling a largely completed attack surface.

This ‘deeper and wider’ attack surface just attaches to the existing problem of how to manage the velocity, volume and complexity of information generated by the myriad of IT and security tools in a firm. The feeds from these disconnected techniques should be analyzed, remediation, and normalized effort prioritized.  The more difficult the challenge, the more tools, and the broader the attack surface, the more data to analyze. Conventionally, this approach required legions to staff to comb during the huge amount of data to connect find latent dangers and the dots. Such efforts took months, for the period of which time attackers utilized vulnerabilities and took out information.

Breaking down existing automating conventional security operations tasks and silos, thus, technology has helped to become a force-multiplier for augmenting scarce cyber security operations talent. In this context, the use of human-interactive machine learning engines can mechanize the aggregation of data across different data types; data of map assessment to compliance requirements; and normalize the information to rule out false- positive, enrich data attributes and duplicates.

Risk Assessment:

Once internal security intelligence is contextualized with external threat information (e.g. malware, exploits, threat actors, reputational intelligence), such finding should be inter-related with business criticality to identify the actual risk of the security gaps and their ultimate impact on the organization.

Eventually, unknowing the impact a ‘coffee server’ has on the business assessed to an ‘email server’, makes it nearly impossible to aim at remediation efforts on what actually matters. In this context, human- interactive machine learning and advanced algorithms play a big role in driving the exact response to individual risks.

Orchestration of Remediation:

Increasing teamwork between security teams that are responsible for  recognizing security gaps and IT operations teams which are focused on remediating them, carry on to be challenge for many firms. Through setting up thresholds and pre-defined policies, groups can also plan remediation actions to fix security gaps in a well-timed trend.

Procuring machine learning to do the heavy lifting in first line security information assessment facilitates analysts to aim at more progressed researches of threats rather than performing strategic information crunching. This meeting of the minds, by which, Artificial Intelligence is applied using a human-interactive approach grasps lots of promise for responding, fighting, and detecting to cyber risks.