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How artificial intelligence is affecting email marketing

Despite the fact that email is far from the newest and most exciting digital marketing channel, it remains one of the most productive for countless companies. Artificial Intelligence (AI) can be used to automate and optimize many aspects of your email marketing program, such as content, send times and frequency. In turn, you can be confident that you’re moving the needle to maximize engagement and conversions. For example, AI could ideally predict the content and offer that are most likely to drive an individual customer to convert, along with the best time of day and the frequency that is most likely to keep them engaged.

Here’s a look at how AI is being applied to email marketing:

Multivariate and A/B Testing

Sophisticated email marketers have been using multivariate and A/B testing for years but AI and ML allow marketers to perform testing in ways that weren’t possible before.

A growing number of technology vendors offer AI-powered testing platforms that enable marketers to create more robust tests, more quickly identify trends and make predictions, and identify subtle differences between tests that might go unnoticed without the assistance of AI.

The subject line and copy optimization

What subject lines and email copy will produce the best results? For years, marketers have struggled to remove the guesswork from creating the perfect email – without much success. Email marketers can let AI determine which subject lines, body copy and calls-to-action recipients are most likely to respond to.

Artificial Intelligence (AI) allows Email Marketing platform to learn what resonates best with a specific marketer’s audience. These platforms then use natural language technology to create subject lines, body copy and calls-to-action that not only sound like they were written by a human but are consistent with the language typically used by the brand.


Send time optimization with AI

When it comes to optimizing the success of an email marketing campaign, few details are too small to ignore. Take send times. For years, marketers have recognized that when they send emails can have a meaningful impact on opens and clicks.

Artificial intelligence, however, offers an even better approach: instead of making big assumptions and creating large segments, it is possible for a machine to learn when each individual recipient is most likely to open an email and then optimize send time on a per-subscriber basis.

Doing this manually would be all but impossible, but it’s easy to work for machines and a growing number of vendors have incorporated it into their platforms.

Manage Promotional Campaigns

Often, brands miss out on revenue opportunities by giving subscribers the wrong promotion or offer. While some subscribers might convert with a lower offer (for example 25 percent off versus 40 percent), others might only engage with an offer when it cuts the price by a certain dollar amount. It’s easy to see how the wrong offer could lead to a loss of revenue for you, but it’s almost impossible to accurately predict the right offer using humans alone.

The right tool can collect and learn from consumer purchase history data over time and determine which types of offers perform best for each subscriber. This might be a combination of a percent off and free shipping, a certain dollar amounts off or nothing at all. Whatever it is, AI technology can help you drive more revenue from your promotional campaigns.

AI is an increasingly important part of marketing automation platforms, as they can help these platforms identify the behaviors and events that should trigger email-based marketing communications, and determine how the messages delivered should be tailored to produce the desired results.

Features Of Latest Version Android Pie 9 With Power Of Artificial Intelligence

Latest Version Android Pie 9 harnesses the power of Artificial Intelligence to give you more from your phone. Now it’s smarter, faster and adapts as you use it. Android Pie is the ninth major version of the Android operating system. It was first announced by Google on March 7, 2018, and the first developer preview was released on the same day. The second preview, considered beta quality, was released on May 8, 2018. The final beta of Android Pie (fifth preview, also considered as a “Release Candidate”) was released on July 25, 2018. The first official release released on August 6, 2018.

History of Android

The version history of the Android mobile operating system began with the public release of the Android beta on November 5, 2007. The first commercial version, Android 1.0, was released on September 23, 2008. Android continually developed by Google and the Open Handset Alliance. And it has seen a number of updates to its base operating system since the initial release.

artificial intelligence

Versions 1.0 and 1.1 were not released under specific code names, although Android 1.1 was unofficially known as Petit Four. Android code names are confectionery-themed and have been in alphabetical order since 2009’s Android 1.5 Cupcake. The most recent version of Android is Android 9 Pie, which was released in August 2018.

Latest Version Android Pie 9 Features with Artificial Intelligence

version android pie 9


  • Accessibility Menu: With Android 9’s new accessibility menu, common actions like taking screenshots and navigating with one hand are now easier for motor-impaired users.
  • Select to Speak – OCR in Camera View: With Select to Speak, you can select text on the screen and the content read aloud. Now, Android Pie 9 has added OCR support for S2S in Camera and Pictures to make the text even more accessible. Simply select text when using the camera or in a picture,  the text highlighted and read aloud.
  • Sound amplifier: This new Accessibility Service makes it easier to understand conversations by dynamically adjusting over 100 settings to boost the audio in scenarios such as a loud restaurant, bar, or concert.

Battery & Brightness

  • Battery Saver: Battery Saver keeps your charge going longer than ever by turning off features like the Always-On display. Plus, you have more control over when it comes on – so you can go further on one charge.
  • Adaptive Battery: This feature uses machine learning to predict which apps you’ll use in the next few hours and which you likely won’t, so your phone only spends battery power on the apps you care about.
  • Adaptive Brightness: With Adaptive Brightness, your phone learns how you set your screen’s brightness in different lighting environments and automatically does it for you over time.
  • Background restrictions: Now, you’ll see recommendations in Settings to restrict certain apps that use too much battery, so you can have more control over your battery.

Latest Version Android Pie 9


  • Multi-camera support: With Android 9, developers can now create immersive experiences using streams from two or more physical cameras, such as on devices with either dual-front or dual-back cameras. Examples include depth, bokeh, stereo vision, and more.
  • External camera support: Android 9 now supports external USB / UVC cameras on certain devices.

Digital Wellbeing

  • Do Not Disturb: Improvements to Do Not Disturb to silence not just notification sounds, but also all the visual interruptions. Calls from starred contacts will still come through, so you don’t have to worry about missing something urgent.
  • App dashboard: Get a daily view of the time spent on your phone, how frequently you use different apps, and how many notifications you get.
  • Wind Down: Set a daily schedule to get your phone ready for bed. Grayscale fades your screen to gray while Do Not Disturb silences notifications for a restful sleep.
  • App timers: App timers let you set daily time limits for your apps. When you reach the limit, the app paused for the rest of the day.


  • Display cutout: Support for devices with cutouts to make use of available screen space.
  • Edge-to-edge screens: Support for devices with 18:9 and taller aspect ratios, and devices with display cutouts

Android Pie 9


  • Multiple users on dedicated devices: Android 9 makes it easy for users to share a single device, good for shift workers or public kiosks.
  • Work tab in the launcher: Now, you can visually separate your work apps. Tap on the work tab to see work apps all in one place, and turn them off with a simple toggle when you get off work.
  • Postpone Over-the-air (OTA) updates: Android 9 now provides the ability for Enterprise IT admins to define freeze periods up to 90 days during which time devices in their fleet will not update the Android OS. This ensures their devices states remain unchanged during a critical time like holidays.


  • Multiple Bluetooth connections: With Android 9, you can connect up to five Bluetooth devices and switch between these devices seamlessly. Incoming phone calls sent to all connected Bluetooth devices that can accept, so you’ll never miss a call.
  • Sound delay reporting: Android 9 offers support for headsets with sound delay reporting. So video on your device and audio on your headphones can always stay in sync.
  • Volume memory per Bluetooth device: Android 9 will now remember the last volume you set for each of your Bluetooth devices. No more blasting music too loudly when you reconnect to your car or headphones.
  • HDR: Android 9 adds built-in support for High Dynamic Range (HDR) VP9 Profile 2, so you can watch HDR-enabled movies on YouTube and Google Play Movies. HDR improves the brightness and color range of video to improve the picture quality and experience.
  • HD Audio: Improved performance and support for HD audio delivering clearer, sharper, and richer quality sound.
  • HEIF: Android 9 now supports HEIF photos on the Android platform to improve compression of pictures and reduce the amount of storage needed.


  • Notification enhancements for messaging: Now, messaging apps can provide suggested ‘smart replies’ in the notification, so you can respond in a tap. Plus, any inline reply drafts won’t disappear if you navigate away. And you’ll be able to see images sent from your friends right in the notification.
  • Manage Notifications: You now have a quick way to turn off notifications from a range of apps. So you only receive those that are helpful to you. You’ll also get a smart prompt if you’re swiping away certain notifications whether you want to keep receiving them.

Pie 9

Privacy & Security

  • Android Backups: Android 9 enables encryption of Android backups with a client-side secret (the device PIN, pattern or password) for greater security.
  • An Android biometric prompt: Android 9 introduces a number of new security features, including a standardized biometric authentication prompt to provide a more consistent authentication experience across Android.
  • The Android Protected Confirmation: On compatible hardware, apps can now use UI controlled by the secure hardware to get your confirmation for a sensitive transaction, such as making a payment.
  • StrongBox: On compatible hardware, apps can now take advantage of tamper-resistant hardware to protect their private keys. Making it harder than ever for malware to steal their credentials.
  • Privacy enhancements: Android 9 safeguards privacy in a number of new ways. Now, Android will restrict access to your phone’s microphone, camera, or other sensors when an app is idle or running in the background. (If an app does need to access a sensor, it will show a persistent notification on your phone.) Android 9 also brings important improvements that protect all web communications and offer private web surfing.

System Usability Enhancements

  • At-a-Glance on Always-on-Display: See things like calendar events and weather on your Lock Screen and Always-on Display.
  • Redesigned Quick Settings: A more consistent user experience for Quick Settings with all toggles. It plus an updated visual design and added informational subtext.
  • Volume controls: Simpler, more accessible volume controls let you control media volume instantly. As well as quickly toggle call and notification volume settings.

latest version Android Pie 9

  • Screenshots: Now, you can take screenshots easily from the power menu and draw, annotate, or crop them quickly.
  • Rotation: Get more control over your phone’s display rotation with a simple button that confirms. When you’d like to change the rotation on your device – even when your orientation locked.
  • New system navigation: Re-design of Android’s system navigation to help make it simpler to search and move between apps. Swipe up from anywhere to see full-screen previews of recently used apps. Swipe left and right to easily navigate between them, and tap on one to jump in.
  • App Actions: App Actions predicts what you’ll want to do next based on your context. And displays that action right on your phone, saving you time.
  • Slices: Interactive snippets of your favorite apps surfaced in different places, like Google Search.
  • Overview Selection: Long-press to select text or image in Overview mode and see actions based on what you’ve selected (for example, an option to route to an address with Google Maps or share for an image).

Avast launches AI-based software to block phishing attacks

Global cybersecurity firm Avast has released an Artificial Intelligence (AI)-based software to block phishing attacks. The software is a free and premium flagship consumer security product, the Prague, Czech Republic-headquartered company said in a statement. The product designed to ensure enhanced detection of the phishing attacks by automatically checking a site’s URL for suspicious tokens, domain meta information, and inspecting the visual aspects of sites.

This technology allows it to recognize new phishing attacks in seconds and protecting users across all platforms from falling victim to phishing scams. This unique technology allows Avast to recognize new phishing sites in seconds. Also, Protecting Avast users across all platforms from falling victim of phishing scams and other fraudulent emails.

Do Not Disturb Mode

Avast’s new Do Not Disturb Mode silences alerts including those from third-party applications, such as Windows, email, chat and browser notifications while users run applications in full screen. Do Not Disturb Mode is a free feature and prevents applications from distracting or embarrassing users while gaming or presenting.

Sensitive Data Shield

Sensitive Data Shield is a feature that protects premium Avast customers with an additional safety net from cybercriminals and spies. The feature identifies sensitive files, such as tax files, health records, and travel documents. And it gives users the option to “shield” and protect access to these files. This way, unauthorized third parties and programs, such as malware, are unable to read and alter the files. And it allowing users to take back control of their sensitive data.

Improved Smart Scan

Avast’s Smart Scan feature combines scans for viruses, software updates, network problems, and performance issues into one concentrated scan. It allows free and premium users to check for a range of issues with just one click. And it has been optimized to scan and identify any problems with the PC, twice as quickly as before.

Enhanced network security

Avast’s Wi-Fi Inspector feature, a free feature which scans routers, PCs, mobile and IoT devices connected to users’ network and provides solutions on how to fix issues found, has been enhanced for improved device identification and more thorough detection of security vulnerabilities and similar weaknesses. The feature displays devices found on the network on a detailed map. Hence Making it easier for people to navigate and control the devices connected to their local network.

So using Artificial Intelligence (AI), Avast 2019 ensures enhanced detection of phishing websites by automatically checking a site’s URL for suspicious tokens, domain meta information, and inspecting the visual aspects of sites.

Investment Management Using Artificial Intelligence (AI): Future of Trading

Portfolio managers make decisions on behalf of investors. Wandering over to the trading desk when they need to access the markets, where dealers will size up the incoming order and call up a reliable bank counterparty to get it done on optimum terms. Within more advanced firms, there may be none of this dialogue, like almost everything. From portfolio management to order entry and execution, done electronically. The humans who remain are merely guardians of the AI (Artificial Intelligence) machines, stepping in when markets get dicey or trades need rerouting.

Automated trading was just the first step

This is a gradual shift that has played out over recent years as automated trading has increased, leveraging Artificial intelligence (AI), and machine-learning techniques to build more intuitive systems that can make trade decisions faster than the blink of an eye. Some investment firms have embraced technology faster than others. But within the next few years, many more could find themselves moving toward the advanced end of the spectrum.

AI offers the potential to automate very low-value repetitive tasks and provide data-driven insights on liquidity and execution. All of which can be very valuable to an investment management trading desk in seeking the best possible deal for investors.

Automated trading is not new, of course. It has been on the rise among the top investment banks for many years, with significant investment in algorithmic tools that used to execute trades according to certain pre-defined criteria. Traders have found they can make cost-savings and reduce market impact in certain circumstances by using smart algorithms rather than relying on human reactions.

AI is investing’s new tech trend of choice

As in other sectors, AI can be used simply to save costs and create efficiencies or it could be used more aggressively to beat the competition. While AI might have the potential to replace human decision-making in fast-moving financial markets. It remains to be seen to what extent financial institutions are willing to hand over the reins to machines.

Artificial Intelligence used simply to save costs and create efficiencies or used more aggressively to beat the competition. The potential for machine-based decision-making on the trading desk now widely accepted. But some believe the investment management function may be the next frontier.

How Artificial Intelligence can drive investment management

Bringing AI to investment management would seem to be a natural progression, however. Automation began originally at the stock exchanges where technology was first used to match buyers and sellers. And after that, it extended gradually to banks with the development of automated trading strategies. But with so many more asset managers than banks, it could take many years for automation to pervade the buy side.

The trading world already highly automated, but applying AI to Investment Management is much more complicated. Markets are always changing, so the strategies that worked yesterday won’t necessarily work tomorrow, and data is much more limited.

Increased adoption of Artificial Intelligence will ultimately rely on individual firms building the necessary knowledge base. And embedding a culture that embraces innovation to progress and competes in modern financial markets. This could well be a gradual, generational shift. Knowledge will be a major barrier because investment firms don’t typically employ large numbers of engineers. And have limited experience in statistics and mathematics, which are key components of AI. Beyond the early adopters, it will be a long time before we see machines replacing humans on a widespread basis.

Be the Superhero for Next Marketing Trend

In the world of digital marketing and social media, it takes more than a funny video or trendy catchphrase for a product to become a hit with consumers. A few years ago it became nearly unthinkable to have a business and industry without having a website for it. That’s still the case, but with the impressive rise of smart mobile technology, it may soon become unthinkable to have a business and the future of digital marketing without having an app.

It’s safe to say that apps are the future of digital marketing and that attention to brand app users will surpass attention to retweets and Facebook likes in importance over the next few years.

Give Your Brand a Voice

The primary reason we expect a lot of changes in this industry is that players are engaged in a cut-throat competition to outdo each other in this contest for consumer attention. It is a healthy competition as it has brought about new ideas and the biggest winner here is the consumer. All these efforts are geared towards enticing consumers more than competitors.

By the end of 2017, there were more than 40,000 Alexa skills alone and more than 44 million Alexa and Google Home devices sold.

Not all Alexa and Google skills are perfect. But this is an amazing push by brands into a new and unknown channel, where there are no real ROI numbers yet to show that voice will be a winner. The adoption and speed of voice-driven conversations are becoming a reality much faster than anticipated.

The answer may be that more brands are now willing to experiment early with technology and feel more comfortable testing new channels like voice and bots.

Future of Digital Marketing

And don’t forget that Google’s Assistant app and Siri do not require a smart speaker. They are more accurate and relevant user data because Google knows your location, movement, and app habits which a smart speaker currently can’t.

The future of Digital Marketing

Virtual reality (VR)

This gives consumers a chance to interact with products in a simulated three-dimensional environment, created using interactive software and hardware technologies.

Future of Digital Marketing

Augmented Reality (AR)

A more advanced form of Virtual Reality. While VR replaces the real world with a simulated one, AR creates a real-time interactive environment in which, a user can digitally manipulate information.

Visual Messaging and less text

Pictures speak better than words. This means future advertisers are bound to use more images as opposed to text. These images and texts passing across information about their products and services.

Future of Digital Marketing

Reliance on Digital Data for Decision Making

Digital Marketing activities generate a lot of measurable data. This same data is useful for marketers when planning for instance, in market segmentation. It would not be a surprise therefore when future marketers heavily rely on these data in their decision making.

Future of Digital Marketing



Wearable Digital Devices

These include smartwatches, fitness trackers, smart clothing, smart jewelry, and implantables. They collect vital lifestyle information/data like a person’s eating habits, heartbeat among other data. This is an essential market information intelligence gathering that helps marketers promptly plan and respond to consumer issues.

Future of Digital Marketing

Human Intelligence vs Artificial intelligence

We have witnessed heated debates on whether Artificial intelligence is superior to Human Intelligence. So the Human Intelligence can be replaced.
Despite these arguments, artificial intelligence is here to stay and professionals will increasingly rely on this. Already we have unmanned drones, robots and computer games among other innovations.

This is only but a small glimpse into the future of Digital Marketing. There will be more invention definitely as the future is bright.

How is AI Technology Used in Digital Marketing

The basic questions of every digital marketer revolve around the messages they put out – what to send, to whom, when and through which channel. With the growth of big data, marketers now have far more information than ever before to get these answer from. However, big chunks of data often end up further complicating the problem. As managers simply don’t have the time or the ability to sift through the data and derive meaning from them. This is where artificial intelligence comes in.

Best Artificial Intelligence Solution

Because of its ability to filter and segment unstructured data and detect patterns in it, AI can identify opportunities and automatically act upon them. And the more an AI system does this, the faster and more accurate it becomes. Over time, the entire execution of an online campaign can be handed over to AI, while managers can focus on aspects of business where human intervention is required, such as innovation and brand growth.

And this isn’t just a futuristic vision. AI in \\ marketing already exists and is making the lives of customers and marketers easier every day.

Search and filtering

In 2015, Google rolled out RankBrain, its new AI engine for processing search results. No longer would search algorithms work on rule-based, easily tweaked metrics. Machine learning can master the search algorithm on its own, guide results towards the most relevant options and give direct responses to direct, conversational queries such as “How old is Jennifer Lopez?”

Natural Language Processing (NLP)

Have Swiftkey enabled on your phone? Then you’ve already used NLP technology. This is a field that focuses on a computer’s ability to learn and be capable of processing the nuances of a human language to the level where it can infer meaning and offer responses. When a machine can understand sentiments and opinions rather than just keywords. Brands can understand and work with customers at a broader level and tailor their responses to what the customer really wants.


AI-powered chatbots are starting to take over traditional live chats, and for good reason. With 24×7 service, the ability to retain and track customer buying information, the ability to handle several requests simultaneously and an always-friendly attitude. AI chatbots can be a game-changer in terms of customer assistance and site engagement.

Predictive analytics

With the help of AI, marketers can extract information from huge datasets. And they can use it to identify user behavior patterns, predict buying trends and devise targeted marketing strategies. For instance, Google’s DoubleClick manager is a pivotal tool for AdWords professionals. It automatically recommends strategies based on the target audience and campaign goals. Again, the Adobe predictive analytics tool analyzes large volumes of data based on predefined business objectives. It uses data mining to create and validate a model, and apply the results of the model into business decisions.

3 Ways Artificial Intelligence benefited Healthcare Industries

Consulting firm Frost & Sullivan reports that the healthcare Artificial Intelligence (AI) market is set to experience a compound annual growth rate of 40 percent through 2021, largely because AI has the potential to improve healthcare outcomes by 30 to 40 percent while simultaneously cutting the costs of treatment in half.

“AI systems are poised to transform how we think about disease diagnosis and treatment,” says Frost & Sullivan Transformational Health Industry Analyst Harpreet Singh Buttar. “Augmenting the expertise of trained clinicians, Artificial Intelligence systems will provide an added layer of decision support capable of helping mitigate oversights or errors in care administration.”

The value of Artificial Intelligence in the healthcare space not limited to clinical settings, however. By facilitating medical diagnostics, improving pharmaceutical marketing, and reducing medication non-adherence, AI-powered technologies are driving much-needed change at nearly every stage of the patient journey.

Facilitating medical diagnostics

Diagnostic errors play a role in around 10 percent of patient deaths and between 16 and 17% of all hospital complications. As exceptionally skilled as most healthcare providers (HCPs) are, in many ways, the human mind remains fallible.

As Andrew Beck, Director of Bioinformatics at Beth Israel Deaconess Medical Center Cancer Research Institute points out, “Identifying the presence or absence of metastatic cancer in a patient’s lymph nodes is a routine and critically important task for pathologists, [but] peering into [a] microscope to sift through millions of normal cells to identify just a few malignant cells can prove extremely laborious using conventional methods.”

That’s why Beck and his team built an automated diagnostic tool using a deep learning algorithm trained to differentiate between cancerous and noncancerous cells. In an evaluation conducted in 2016, the automated tool achieved a diagnostic success rate of 92 percent — just 4 percentage points lower than human pathologists. What’s more, when Beck’s team combined human pathologists’ analyses with the analyses of the automated tool, the diagnostic success rate rose to a remarkable 99.5 percent.

Ultimately, Beck believes that his experiment barely scratches the surface of what a hybrid — that is, human and algorithmic — approach has to offer to medical diagnostics. “Our results…show that what the computer is doing is genuinely intelligent and that the combination of human and computer interpretations will result in more precise and more clinically valuable diagnoses to guide treatment decisions.”

Improving healthcare marketing

Once a patient has been diagnosed, the next step is to find a therapy that will cure — or at least mitigate the effects of — their condition. HCPs obviously have an out sized influence over which therapeutic regimen a patient adopts, but the importance of “Ask your doctor about [Drug X]” direct-to-patient messaging shouldn’t be underestimated.

Unfortunately, the pharmaceutical sector often finds itself talking past its core constituencies. In fact, one study found that as many as 45% of patients believe that pharmaceutical companies don’t understand their real needs. Not unlike the challenges of traditional medical diagnostics, this disconnect is first and foremost a problem of scale.

In the digital age, gauging patient behavior — the first step toward delivering relevant, tailored messaging — involves aggregating information drawn from a wide variety of data sets, including medical data like hospital records, lab results and HCP notes and general data like media preferences, internet usage, and demographic information. Healthcare marketers must then draw out salient narratives and insights from their aggregated data — “connecting the dots,” so to speak — not just once, but on a rolling basis over the course of a campaign.

The reality is that executing such a data-driven approach at scale requires a superhuman amount of computing capacity. Not even the best, most experienced team of marketers is capable of organizing and analyzing millions of data points, which is where machine learning-based predictive analytics tools become invaluable.

By leveraging a properly-trained predictive analytics algorithm, a marketing team can gain unparalleled insight into their target patients, facilitating messaging based not on broad-strokes segmentation, but on analyses of the intricate — and often imperceptible to the human eye/mind — ways that a patient’s past behavior, personal characteristics and current position in the patient journey interact.

Reducing medication non adherence

Between 1988 and 1994, roughly 38 percent of adults living in the United States were taking at least one prescription drug. Over the subsequent two decades, that figure grew to 49 percent, driven in large part by a 100 percent increase in the number of adults taking three or more prescription drugs.

All told, according to research presented to the American Hospital Association in October 2016, “Total net spending on prescription drugs…has accelerated over the past year to $309.5 billion annually, making prescription drugs the fastest growing segment of the U.S. healthcare economy.”

A significant fraction of this $309.5 billion is going to waste. As many as half of the 3.2 billion prescriptions written in the U.S. each year aren’t taken as directed — if they’re even taken at all. This non adherence leads to over $250 billion dollars of unnecessary costs or roughly 13 percent of the country’s total annual healthcare expenditures.

But just as pharmaceutical marketers can use algorithmic tools to refine their patient targeting, HCPs can use algorithmic tools to reduce this systemic waste by getting a better sense of which of their patients are most prone to medication non-adherence. Everything from demographics and payer type to out of pocket costs and the prescribing HCP’s area of specialty bear upon the likelihood of a patient deviating from their prescribed regimen and an Artificial Intelligence-based approach is a robust way to take all of these factors into account.

Armed with the predictive outputs of such systems, HCPs are able to pinpoint which patients need additional support in order to remain on course with their treatment. Granted, better, more targeted communication isn’t a comprehensive solution for medication non-adherence, but research published in Medical Care suggests that poor HCP-patient communication results in a 19 percent higher risk of non-adherence. In other words, it’s a start.

Overview of the Medical Artificial Intelligence (AI) Research

Recently AI techniques have sent vast waves across healthcare, even fueling an active discussion of whether AI doctors will eventually replace human physicians in the future. We believe that human physicians will not be replaced by machines in the foreseeable future. But AI can definitely assist physicians to make better clinical decisions. The increasing availability of healthcare data and rapid development of big data analytic methods have made possible the recent successful applications of Artificial Intelligence in healthcare. Guided by relevant clinical questions, powerful AI techniques can unlock clinically relevant information hidden in the massive amount of data, which in turn can assist clinical decision making.

Here you can understand how Artificial intelligence Works.