Self-driving AI clinic reimagines healthcare for the 21st century


Seattle-based design firm Artefact Group has revealed a comprehensive concept that would make the future of healthcare mobile. Integrating passive monitoring technologies in the home, a smartphone app, AI diagnostics and a self-driving clinic, the system combines a variety of innovations for a new spin on healthcare.

While many sectors of society are being dramatically disrupted by rapidly evolving digital innovations, the arena of healthcare seems to responding more slowly, with many hospitals still largely relying on paper to record patient data. Earlier in the year we saw a gadget-filed, subscription-based medical clinic open in San Francisco, and several fascinating advances are occurring in the field of artificial intelligence diagnostics, But the Aim concept envisions a fundamentally different healthcare approach than what we have been used to for the past 100 years.

The system begins with a series of active testing and passive monitoring devices in the home, capturing data from several sources, such as the bathroom scale, toilet and medicine cabinet. The goal is to create an interconnected set of devices, including health-monitoring wearables, that can create a unified, patient-owned health record.

A constantly learning AI would then monitor a person’s health data and flag unusual results. When needed, a self-driving mini clinic could navigate to your location for more comprehensive diagnostics, such as thermography, breath analysis, and respiration or cardiac rhythm.

Inside this mobile clinic, an AI could offer its diagnosis, and even deliver common pharmaceuticals such as antibiotics or contraceptives. If a health condition is flagged as serious or escalating, the Aim system would then connect the patient to an on-call specialist or even transport them directly to a hospital emergency room.

“The mission of Aim is to close the data, experience and logistical gaps between home and clinical environments,” the designers say.

Despite being a slightly pie-in-the-sky concept right now, rapid advances in personal health monitoring and AI means it’s not necessarily that far from being feasible, and much of the Aim system feels like it could be pragmatically implemented into our current healthcare processes without too much trouble. With the current burden on patients to get to doctors’ clinics, which can sometimes be quite far away, an integrated monitoring system such as this could lighten the load for overworked healthcare workers.

AI-driven diagnostic tools are also set to inevitably become increasingly useful for low-risk patient monitoring, and a mobile autonomous clinic could significantly reduce the drain on current hospital resources by catching conditions early before they become serious enough to require a hospital admission.

Cost is of course a major consideration here and developing such a sophisticated system wouldn’t be cheap, but as the costs of healthcare continue to skyrocket maybe some outside-the-box thinking such as this is should be encouraged. Much like the San Francisco Forward clinic, a cost-effective subscription-based system could possibly offer many who currently can’t afford big health insurance premiums greater access to medical care.


5 Facebook Bots To Support Your Health


HealthTap — A Doctor Bot

HealthTap is a larger health company that decided to democratize their wealth of health information by creating a chatbot.

You can ask all your burning medical questions here and get resources from HealthTap’s large database, as well as personalized responses from doctors! No more waiting rooms, the chatbot will see you now.

Atlas — A Fitness Bot

Atlas knows how hard it can be to keep up with a regular workout routine when your days are getting swamped.
Maybe not for pro-athletes but definitely for fitness enthusiasts of all kinds, Atlas is free and has more than a few tricks up his sleeve to keep you engaged with your workouts. This bot is currently in beta and sends personalized workout reminders on a schedule you provide along with motivational quotes (#justdoit). Very promising concept inside a bot and the Atlas makers plan to expand into workout plans and fitness tips very soon! Stay tuned.

Woebot — A Mood Bot

Woebot is a mood tracking bot with personality and a conversation designed that feels like talking to a bot therapist.
Backed by scientific research, Woebot can help reduce depression, share CBT resources, and learns from your conversations over time. The Woebot makers offer scalable pricing for individuals and the first 14 sessions are totally free.

Forksy — A Nutrition Bot

Forksy keeps track of your meals so you don’t have to. Whether you had three slices of pizza or a bagel with a little too much cream cheese, Forksy knows the dirty secrets of your diet. If you’re trying to be more health conscious, Forksy is a great option. The NLP capabilities are great and it feels as if you can just type in any food combination and get an instant result.

Izzy — A Period Tracker Bot

Izzy helps women track their periods and sends reminders to take birth control pills. This chatbot has a fun personality and tries to turn a not-so-fun topic into something more friendly and manageable.
It would be great to see clever NLP for topics unrelated to menstruation but Izzy takes on a great use case to bring chatbots closer to women.

Why Chatbots & Health? — Key Takeaway

Health apps and wearable devices took the world by storm, supporting users throughout their daily activities. It seemed normal in the era of the app store to download and try a couple of new apps on a weekly basis but app downloads have been steadily decreasing over the past years.

Chatbots are booming and bot developers are finding more use cases in different health industries. Some of the bots mentioned above are not as in-depth and far-reaching as their app competitors but chatbots in general seem to be a great solution for simple activities and quick feedback.

Why? There’s no need to require a Facebook user to leave Facebook and open another application to support a simple task. Chatbots don’t require that.

Brief explainer: I’m referring to Facebook’s current challenge to retain its users on the Facebook application and not lose them to other apps such as a fitness application when a user wants to get workout suggestions.

Implementing chatbots on Facebook creates a retention ecosystem, something that Facebook’s Chinese competitor WeChat has mastered. Users don’t have to leave Facebook anymore.

With such seamless yet effective interactions, chatbots are here to make our lives easier in different ways. The list above shows us that chatbots can help us stay on top of our fitness routine, track periods, track moods, provide us with dietary feedback, connect us with doctors and a lot more.

It seems inevitable that we will see a wave of chatbots disrupting the health space (& other industries) with users finding more ways to support their daily activities within the platforms they spend most of their time on such as Facebook.


The Human Army Using Phones to Teach AI to Drive


As her fellow patients read dog-eared magazines or swipe through Instagram, Shari Forrest opens an app on her phone and gets busy training artificial intelligence.

Forrest isn’t an engineer or programmer. She writes textbooks for a living. But when the 54-year-old from suburban St. Louis needs a break or has a free moment, she logs on to Mighty AI, and whiles away her time identifying pedestrians and trash cans and other things you don’t want driverless cars running into. “If I am sitting waiting for a doctor’s appointment and I can make a few pennies, that’s not a bad deal,” she says.

The work is a pleasant distraction for Forrest, but absolutely essential to the coming ages of driverless cars. The volume of data needed to train the AI underpinning those vehicles staggers the imagination. The Googles and GMs of the world rarely mention it, but their shiny machines and humming data centers rely on a growing, and global, army of people like Forrest to help provide it.

You’ve probably heard by now that almost everyone expects AI to revolutionize almost everything. Automakers in particular love this idea, because robocars promise to increase safety, reduce congestion, and generally make life easier. “The automotive space is one of the hottest and most advanced fields applying machine learning,” says Matt Bencke, CEO of Mighty AI. He won’t name names, but claims his company is working with at least 10 automakers.

The challenge lies in teaching a computer how to drive. The DMV rule book provides a good place to start, because it covers rudimentary things like “Yield to pedestrians.” Ah, but what does a pedestrian look like? Well, a pedestrian usually has two legs. But a skirt can make two legs look like one. What about a fellow in a wheelchair, or a mother pushing a stroller? Is that a small child, or a large dog? Or a trash can? Any artificial intelligence controlling a two-ton chunk of steel must learn how to identify such things, and make sense of an often confusing world. This is second nature for humans, but utterly foreign to a computer.

Cue Forrest and 200,000 other Mighty AI users around the world.

The onboard cameras helping prototype robocars navigate the world photograph almost every environment and circumstance you can image. Automakers and tech companies send those photos by the millions to an outfit like Mighty AI, which makes a game of identifying everything in those photos. It sounds tedious, but Mighty AI makes it a 10 minute task with points, skills, and level-ups to keep it engaging. “It’s more like Candy Crush than a labor farm,” says Bencke. The monetary rewards, although small, help, too.

Forrest carefully draws a box around every person in each picture, then around every approaching car, and then around the tires on each car. That done, she zooms in, and working pixel-by-pixel, meticulously outlines things like trees. Click click, click. She selects a different color pointer and highlights traffic lights, a telegraph pole, a safety cone. When she’s finished, the scene is annotated in language a computer understands. Engineers call it a “semantic segmentation mask”.

The need for accuracy makes for painstaking work, but Forrest, who makes a few centers per picture, enjoys it. “It’s like why some adults color,” she says. “It’s become a relaxing task.”

Those millions of annotate photos help an AI identify patterns that help it understand, say, what a human looks like. Eventually the AI grows smart enough to draw boxes around pedestrians. People like Forrest will help double-check the AI’s work. Over time, AI will grow smart enough to reliably identify, say, kangaroos.

Relying on an army of amateurs might seem odd, but it remains the most efficient way of training AI. “It’s pretty much the only way,” says Premkumar Natarajan, who specializes in computer vision at the USC Information Sciences Institute. He’s been working in the field for more than two decades. Although there’s been some promising research into so-called unsupervised learning where computers learn with minimal input, but for now the intelligence in artificial intelligence depends on the quality of the data its trained on.

Bencke says his platform uses its own machine learning to determine what each member of the Mighty AI community is best at, then assign them those jobs. No one is getting rich doing this essential work, but for Forrest, that’s beside the point.

She says she made about $300 last year, money she put toward online shopping. She’s never seen an autonomous vehicle, much less ridden in one. But knowing that she’s helping make them smarter will make her more likely to trust the technology when she finally does.

Source: Wired

How governments are adopting modern business intelligence

Data analysis company Tableau calls on state and local government leaders to embrace modern business intelligence platforms to help scale services more efficiently.

Efficiency and scalable impact might not be the first things that come to mind when you think of government. A basic, and inherent connotation is to think of government as slow and bureaucratic. But that’s the old paradigm — the path without data.

In 1995, when former President Bill Clinton signed the Government Performance and Results Act (GPRA) into law, federal agencies began shifting their strategy to measure and report on program performance. Data, not gut feel, became the new foundation for improving citizen services, increasing accountability, and driving mission goals.

Twenty years later, the shift to data is further amplified in part due to additional legislation, like the Digital Accountability and Transparency Act (DATA), signed into law by former President Barack Obama in 2014. This mandated transparency — where all Federal agencies are required to share data sources, critical insights and reports on matters like budget spend with the public — is gaining traction. However, factors beyond legislation are pushing governments to become more data-centric.

The newest catalyst driving governments to a data-driven approach is the emergence of modern business intelligence (BI), a methodology that empowers everyone within an organization to access and analyze the data they need. This modern, self-service approach to analytics enables an easier and faster way for both employees and leaders to measure performance metrics across every program in the agency.

Mark Russell, a contracted analyst and systems administrator at the Florida’s Department of Juvenile Justice (FDJJ), is one of those government leaders changing the way people think about data-led government efficacy. By turning to self-service analytics, Russell is working to empower the government workers in his agency with a 360-degree view of juvenile offenders that are at risk of falling deeper into the system. By giving everyone access to data and insights, workers are better equipped to take action faster.

“When [our data-driven program] works, people develop an expectation that we can get stuff done. That reputation contributes to a view of good government. It means lawmakers trust our input when developing bold juvenile justice reform policies, and have faith in us to carry out those policies. We’re delivering outcomes for the ‘business’ of government,” Russell said.

In the past, when governments relied on traditional BI, IT managed the reporting queue and struggled to keep up with business questions — making timely and trustworthy insights almost impossible.

For the FDJJ, compiling a detailed report about every juvenile offender and their current standing within the system used to take up to four to five months to create. When Russell’s team implemented a modern business intelligence platform, the speed to insight was reduced to two days.

The FDJJ also used self-service data visualization to create the Prolific Juvenile Offenders dashboard, which delivers a complete view of Florida’s most at-risk juveniles. This dashboard enables everyone in the FDJJ, from caseworkers to agency leaders, to drill down into the specifics and understand where an individual is physically located, what offenses they committed, and what treatments they are receiving. The dashboard was further enhanced by a data-sharing agreement with the Department of Children and Families (DCF). Adding this additional layer of transparency allows an even better view into at-risk youth and helps coordinate intervention strategies between the FDJJ and DCF.

Additionally, the FDJJ uses insights from this dashboard to directly influence policy by showing legislators and other stakeholders the impact policy changes have on the budget, and ultimately the at-risk youth. For example, when juveniles are in the community, the visibility from the dashboard triggers more contact from caseworkers and parole officers. And because the dashboard is updated every six hours, workers in the field — like parole officers and even direct supervisors — have real-time information to effectively and quickly manage caseloads.

The Florida Department of Juvenile Justice isn’t alone in its success with modern BI. Governments around the world are using modern analytics platforms like Tableau to deliver more with less. With modern BI, anyone in a government agency can use data to see and understand exactly how programs are performing. And the results are amazing.


Describing Modern Data Management to my Mom

For Mother’s Day this year, I am inviting the women (and men) in my life to a belated celebratory dinner, as soon as I fly back to the Bay Area later this month. As someone whom I turn to for practical advice from time to time, my Mom rarely asks me to explain things to her. However, when I called her today to wish her a happy Mother’s Day, I not only thanked her for her unwavering support, but also described to her what the company I work for does, and why Modern Data Management matters.

Our conversation went something like this:

So Mom, you know how your cell phone provider charges you every month for the family plan, and sends you an email promotion every so often? Large organizations like them collect information about you and your family members to recall people, data usage and charges per phone number.

Different departments within the telephone company use different systems to save your information, such as your name and billing address. They also keep records of the times you called or sent them an email. Different departments, like order processing and customer support may store your information in different systems that do not talk to one another. For instance, should you call the customer support number on your bill, that department will collect the information that you give them in a different system than if you were to log into the online portal to manage your account.

Oftentimes, different systems have different information about you and your family members from different time periods. This is a problem because every department in the telephone company may have a piece of information about you, but none will have the complete picture. Do you remember the last time you ordered a cell phone online, and then called to change the color? It took the telephone company a while to locate your order. This problem will only get worse as they acquire more organizations, and add more systems and ways of communicating with you (email, phone, website, Facebook, Twitter, direct mail), because your information will be spread into even more systems. In order to provide consistent customer service, all communication channels and departments, like sales, marketing and customer support must have access to the same, consolidated customer information.

Organizations like telecommunications service providers and retailers use Reltio’s Modern Data Management technologies to build applications that provide a 360° view of customers like you. Our technology provides a way to connect to all systems from all departments, and create consolidated profiles with reliable customer information. This reliable information is then made available to all business and analytics applications used by all departments. Reliable information ensures a consistent customer experience across channels and departments, and builds trust and loyalty with customers. So, the next time you call them, you won’t have to repeat what you ordered or what type of data plan you have, depending on whether you use an iPhone or an Android device. They will have that information readily available. We also help organizations understand and manage relationships. Like Facebook, where people can connect to one another and follow their favorite stores and restaurants, we help organizations understand how people are related to each other, and to other organizations and locations through a graph. This helps organizations, like our cell phone provider understand our household needs.

Another reason why Reltio’s platform is modern, is because it uses your profile information to analyze whether your information is correct and complete. We use machine learning and predictive analytics for that. Machine learning make programs “smarter,” by allowing them to automatically learn from the data you provide. Predictive analytics takes information from existing data to find patterns and predict future outcomes and trends. Machine learning and predictive analytics form a recommendation system that recommends satellite TV service or a new phone accessory after learning about your tendencies and desires. These intelligent recommendations help people in marketing and sales determine which promotion to send you, on which channel (email, phone, USPS), at which time. That’s pretty much the gist of it. See you later this month!

At Reltio, our core mission goes beyond MDM. We are focused on simplifying all aspects of data management for IT, while delivering high value data-driven applications into the hands of frontline business users. Reltio Cloud achieves this by combining MDM with multichannel interaction data, predictive analytics and machine learning, all within a unified Modern Data Management platform that operates at Internet scale leveraging big data.


Using Artificial Intelligence to Reduce the Risk of Nonadherence in Patients on Anticoagulation Therapy

Researchers are using VR to make dentist visits less painful

Patients in a study reported less pain, as long as they viewed nature scenes.

Like airlines, dentists understand that the more they can distract you from what they’re doing, the better off everyone will be. UK researchers wanted see if virtual reality can ease patient pain and anxiety, so they enlisted 79 people who needed a tooth pulled or cavity filled. Patients were divided into three groups: One that viewed a VR coastal scene, one a VR city, and the other, no virtual reality at all.

The result? Folks that viewed the ocean VR experienced “significantly less pain” than the other two groups, showing its therapeutic potential for stressful events. Furthermore, follow ups showed that the coastal VR patients experienced less “recalled pain” memories after the fact.

Notably, the city VR was no more effective at reducing patient pain and stress than no VR, so the trick seems to depend on using calming scenes. While that seems incredibly obvious, the psychologists thought VR could just be distracting patients from all the drilling and poking, much as a TV does, but that proved not to be the case. “Our findings are in line with literature, showing that contact with nature, even indirect contact through windows, can influence physical and mental well-being,” the paper explains.

The researchers note that in previous studies, VR has been shown to reduce patient dependence on pain medication. “Our research supports the previous positive findings of VR distraction in acute pain management, and suggests that VR nature can be used in combination with traditional [medication].” The next step, they suggest, would be to vary the content of natural environments (using a forest instead of a coastal scene, for instance) to see if the can determine exactly how it reduces pain. We’d recommend they check out the zen content out there, and avoid any games.