How AI/ML Steered Major Innovations in Medicine & Healthcare In 2020

Of all the innovations in artificial intelligence and machine learning space this year, the most significant ones have turned out to be in the healthcare and medicine field, the credit of which could be given to the unprecedented pandemic situation around the world. In this article, we discover some of the major breakthroughs in 2020.

Read more: https://analyticsindiamag.com/how-ai-ml-steered-major-innovations-in-medicine-healthcare-in-2020/

#ml #ai #innovation #artificial-intelligence #heathcare

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How AI/ML Steered Major Innovations in Medicine & Healthcare In 2020

Of all the innovations in artificial intelligence and machine learning space this year, the most significant ones have turned out to be in the healthcare and medicine field, the credit of which could be given to the unprecedented pandemic situation around the world. In this article, we discover some of the major breakthroughs in 2020.

Read more: https://analyticsindiamag.com/how-ai-ml-steered-major-innovations-in-medicine-healthcare-in-2020/

#ml #ai #innovation #artificial-intelligence #heathcare

Citrix Bugs Allow Unauthenticated Code Injection, Data Theft

Multiple vulnerabilities in the Citrix Application Delivery Controller (ADC) and Gateway would allow code injection, information disclosure and denial of service, the networking vendor announced Tuesday. Four of the bugs are exploitable by an unauthenticated, remote attacker.

The Citrix products (formerly known as NetScaler ADC and Gateway) are used for application-aware traffic management and secure remote access, respectively, and are installed in at least 80,000 companies in 158 countries, according to a December assessment from Positive Technologies.

Other flaws announced Tuesday also affect Citrix SD-WAN WANOP appliances, models 4000-WO, 4100-WO, 5000-WO and 5100-WO.

Attacks on the management interface of the products could result in system compromise by an unauthenticated user on the management network; or system compromise through cross-site scripting (XSS). Attackers could also create a download link for the device which, if downloaded and then executed by an unauthenticated user on the management network, could result in the compromise of a local computer.

“Customers who have configured their systems in accordance with Citrix recommendations [i.e., to have this interface separated from the network and protected by a firewall] have significantly reduced their risk from attacks to the management interface,” according to the vendor.

Threat actors could also mount attacks on Virtual IPs (VIPs). VIPs, among other things, are used to provide users with a unique IP address for communicating with network resources for applications that do not allow multiple connections or users from the same IP address.

The VIP attacks include denial of service against either the Gateway or Authentication virtual servers by an unauthenticated user; or remote port scanning of the internal network by an authenticated Citrix Gateway user.

“Attackers can only discern whether a TLS connection is possible with the port and cannot communicate further with the end devices,” according to the critical Citrix advisory. “Customers who have not enabled either the Gateway or Authentication virtual servers are not at risk from attacks that are applicable to those servers. Other virtual servers e.g. load balancing and content switching virtual servers are not affected by these issues.”

A final vulnerability has been found in Citrix Gateway Plug-in for Linux that would allow a local logged-on user of a Linux system with that plug-in installed to elevate their privileges to an administrator account on that computer, the company said.

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The Trending Healthcare App Features for 2020

The recent technological trend in the healthcare industry has brought a virtual doctor into many of our pockets. Be it a serious health condition or a need to track our fitness level, there are thousands of mHealth apps for most of the healthcare use cases.

In 2020, the health-tech industry offers many mHealth apps ranging from heart rate monitoring to nutrition and fitness apps. Undoubtedly, there will be variation in the app functionality according to the target market, customer base and the purpose.

Use-Case specific app features

There are thousands of healthcare mobile apps available in the market and depending on the use-cases, they will incorporate specific features that help them serve the purpose. Following are some of the most trending app features.

Digital Prescription and Reports

Almost every hospital or pharmacy-related healthcare app should have the functionality to handle digital prescriptions and reporting. Misplacing or losing medical prescriptions and reports is very common for the patients. It even becomes a hassle for the healthcare institutions or doctors to manage and access the patient files. This is where the digital prescription feature comes handy for both the patients and doctors.

This feature should also incorporate the functionality to download the reports and prescription information in a documented format. It allows the patients to manage their lifetime medical history in one place. This feature is very crucial to speed up the medical treatment process.

Wearable Connectivity

Wearables are the most trending discussion in the health tech space. Up until now, this feature is most commonly used by fitness tracking apps. But as the healthcare industry has now paced up the technology adoption, healthcare providers and medical practitioners have started to trust the wearable technologies to monitor their patient health continuously.

In 2020, wearables do not just mean some gadgets like Fitbits. There are many clinical-grade IoMT (Internet of Medical Things) devices used by the healthcare industry that are used in a form of belts, chest straps etc.

The wearable connectivity feature allows the healthcare apps to record the user’s data, which can be shared with the doctors. The doctors can provide a better consultancy if they have access to their patient’s all-time health status.

On-Demand Medicine

Similar to amazon for x apps, this on-demand app feature is focused on making the medicines accessible anytime, anywhere. Using this feature, the patients will be able to refill their stock of medicine without having to visit the pharmacy.

The feature would require the functionality to allow admin to list out the pharmacies in the locality, so that the users can order from the nearest one. To make this feature more effective, you also would need to add an online payment feature within the app.

#healthcare #health-tech #health-tech-and-cyber-security #healthcare-apps #healthcare-application #healthcare-mobile-apps #healthcare-trends-in-2020 #top-healthcare-trends

Importance of AI in Healthcare Sector

AI and related advancements are progressively playing the role of a disruptor in business and society. The application of AI is also increasing in the healthcare domain. These advances can possibly change numerous parts of patient care, just as regulatory procedures inside supplier, patient experience, and pathology labs.

There are as of now various researches recommending that AI can proceed just as or better than people at key human services, for example, diagnosing the ailment. Today, algorithms are beating radiologists at spotting harmful tumors. They are directing specialists on how to build companions for expensive clinical preliminaries.

Nonetheless, for an assortment of reasons, we accept that it will be numerous prior years AI replaces people for wide clinical procedure areas. In this article, we portray both the potential that AI offers to mechanize parts of care and a portion of the hindrances to the fast execution of AI in social insurance.

#artificial intelligence tutorials #ai applications in healthcare #ai in healthcare #applications of ai in healthcare #artificial intelligence and healthcare

Learning AI/ML: The Hard Way

The Wave and the Curve

Data science, Artificial Intelligence (AI), and Machine Learning (ML), since last five to six years these phrases have made their places in Gartner’s hype cycle curve. Gradually they have crossed the peak and moving toward the plateau. The curve also has few related terms such as Deep Neural Network, Cognitive AutoML etc. This shows that, there is an emerging technology trend around AI/ML which is going to prevail over the software industry during the coming years. Few of their predecessors such as Business Intelligence, Data Mining and Data Warehousing were there even before these years.

Finding the Crystal Ball in the Jungle

Prediction and forecasting being my favorite topics, I started finding a way to get into this world of data and algorithms back in early 2019. Another driving force for me to learn AI/ML was my fascination on neural networks that was haunting me since I started learning about computer science. I collected few books, learned some python skills to dive into the crystal ball.

While I was going through the online articles, videos and books, I discovered lots of readily available tools, libraries and APIs for AI/ML. It was like someone who is trying to learn cycling and given a car to drive. Due to my interest in neural networks, I got attracted to most the most interesting sub-set of AI/ML, Deep Learning, which deals with deep neural networks. I couldn’t stop myself from directly jumping into Google Tensorflow (a free Google ML tool) and got overwhelmed by a huge collection of its APIs. I could follow the documentation, write code and even made it work. But there was a problem, I was unable understand why I am doing what I am doing. I was completely drowning with the terms like bios, variance, parameters, feature selection, feature scaling, drop out etc. That’s when I took a break, rewind and learn about the internals of AI/ML rather than just using the APIs and Libs blindly. So, I took the hard way.

On one side, I was allured by the readily available smart AI/ML tools and on the other side, my fascination on neural networks was attracting me to learn it from scratch. Meanwhile, I have spent around a month or two just looking for a path to enter the subject. A huge pool of internet resources made me thoroughly confused in identifying the doorway to the heart of puzzle. I realized, why it is a hard nut for people to learn. Janakiram MSV pointed out the reasons correctly in his article.

However, some were very useful, such as an Introduction to Machine Learning by Prof. Grimson from MIT OpenCourseWare. Though its little long but helpful.

#machine learning #ai #artificial intelligence (ai) #ml #ai guide #ai roadmap