The Futuristic Visit To The Physician Is Here!

Source: IUVM TECH

The world is in the midst of a gigantic 'data revolution' right now.  What does that entail?  There is a massive collection of data going on around us at any given moment.  From the geographical location at which you are located to the subject matter which you are searching for using a search engine such as Google or Bing.  What benefits might arise out of such a revolution?  Many have been proposed.  The overall concept to understand why such benefits arise was written about in an article titled "The 7 Industries That Benefit Most From Big Data" on the website 'Smart Collective' in 2016:

Generally, the more data you have, the more specific and accurate insights you’ll be able to generate, which is why big data has become such a powerful tool (and buzzword) in recent years

More data points equals more accuracy.  Which promotes the largest benefit which serves as a feedback into all of the industries mentioned in the article above:  'artificial intelligence.' A pathway toward the benefits of artificial intelligence exists and is currently being taken by technology groups around the world.  On this pathway toward 'artificial intelligence' playing a larger role in our society has been the concept of 'deep learning':

Deep learning (also known as deep structured learning or hierarchical learning) is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms. Learning can be supervised, semi-supervised or unsupervised.[1][2][3]

Deep learning architectures such as deep neural networks, deep belief networks and recurrent neural networks have been applied to fields including computer vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, bioinformatics, drug design, medical image analysis, material inspection and board game programs, where they have produced results comparable to and in some cases superior to human experts.[4][5][6]

Deep learning models are vaguely inspired by information processing and communication patterns in biological nervous systems yet have various differences from the structural and functional properties of biological brains (especially human brains), which make them incompatible with neuroscience evidences.[7][8][9]

Again, the amount of data which serves as an 'input' will greatly affect the accuracy of the 'output' the intelligent (computation) answer given to us after the algorithm is executed.



How does all of this play out in the immediate future?



One example is the field of medicine.  During a recent break, I was perusing through Facebook and found the following video by an organization called 'Forward'.  The video below gives us a glimpse into technology which has already been developed and is out on the market right now.  A glimpse of a 'future visit to the doctor' for a health check up.  The video is less than 10 minutes in length and worth watching.

Wow right?  For those who are uninterested in viewing the entire video here are the basics:


1) No receptionist to check in with.  Just an equivalent of an iPad.

2) A Body scan with infrared radiation.  While placing a single hand on a sensor, blood oxygen levels, heart rate, metabolic rate, and a body composition -- fat tissue, muscle and bone tissue.

3) Up to 3 visits normally to the center per month.  Although, a patient may come and get a body scan anytime.  Remember, more data more accuracy.

4) A Body scan creates a 3D model of your body.

5) The Information gathered in the body scan is synced with exam room digital display (i.e. monitor, tv screen) at which time the patient can view results with a physician.  Additionally, the information is also synced with the mobile app on your smartphone.

6) Patient goes into exam room and discusses data.

7) Patient and physician review body scan data and blood work (all on the same day) to come up with a plan to achieve health goals which lead to better health.

8) Planning is individual based.  No two plans are equal.



Having the ability to reduce time or redundancy with having an on site laboratory (for blood work), a visit to the 'futuristic physician' provided by 'Forward' is greatly enhanced.  Plus, as pointed out in the video above, the language which enters into the patient file is the patient's own language -- which is recorded on the screen during discussion with physician.  Additionally, all data and discussion is forwarded to your mobile app for your personal viewing and stay plugged into continuously.  Awesome.  This is the future of medicine.



Conclusion...



The data revolution has the ability to transform our daily lives in many ways.  As shown in the video above, the access of big data in real-time is effective in treating an individual patient with the patient's own needs based on the data collected.  Additionally, that data is compiled with the ability (upon patient approval) to be used in conjunction with other patients for research and discovery purposes.



One main obstacle with the deluge of big data are the different file types in which the data exists currently.  In order to make meaningful discoveries using the big data files, the processing/algorithms need to be able to read the file format.  With the collection of data in this forma (a single format), this represents a solution to an existing problem.



Of course, that means still processing old data from decades in the past.  Although, after processing old data and combining it with new data compiled in the new format, powerful advances will be able to be made by mining the data for medical research and drug discovery purposes (to name just two).  The future of medicine is truly exciting and should be embraced by each of us.



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Parameters: Amazon Go Will Seek To Understand How You Feel About A Grocery Product?

Source: China Brands

Technology has served many different functions in our society.  Among the most important recently are the algorithms which correct themselves while directing people around the world.  Yes, I am talking about the residents of the world who use 'GoogleMaps'.  Over time, the algorithm seeks to improve the accuracy by self assessment.  What? Yes, the algorithm updates and assesses itself after every use.  Amazing.  Back in January in Seattle, Amazon opened up a store without cashier type check out stands.  Yes, without check out stands.  I have been sitting on this short post for quite a while for no good reason.  Although, with the greater use of digital tracking of our preferences, the subject is worth highlighting.

Do I Really Love That Food?

Back in January, an article in 'The New York Times' titled "Inside Amazon Go, a Store of the Future"

But the technology that is also inside, mostly tucked away out of sight, enables a shopping experience like no other. There are no cashiers or registers anywhere. Shoppers leave the store through those same gates, without pausing to pull out a credit card. Their Amazon account automatically gets charged for what they take out the door.

There are no shopping carts or baskets inside Amazon Go. Since the checkout process is automated, what would be the point of them anyway? Instead, customers put items directly into the shopping bag they’ll walk out with.

Every time customers grab an item off a shelf, Amazon says the product is automatically put into the shopping cart of their online account. If customers put the item back on the shelf, Amazon removes it from their virtual basket.  

The only sign of the technology that makes this possible floats above the store shelves — arrays of small cameras, hundreds of them throughout the store. Amazon won’t say much about how the system works, other than to say it involves sophisticated computer vision and machine learning software. Translation: Amazon’s technology can see and identify every item in the store, without attaching a special chip to every can of soup and bag of trail mix.  

Before the above excerpt can be explored more, the differences between a traditional grocery store and the new store offered by Amazon should be briefly highlighted.  Grocery stores with the option of 'cashier assisted' checkout are nothing new.  Stores ranging from Ralphs to Home Depot (or Lowes) have all incorporated the 'checker' less option.  What is new is the option without a 'check out stand' altogether.  To test your ability of paying attention to the potential impact of opening a store such as that which has been open for over a few months now, there are a few questions which a school teacher came up with in "teacher has come up with questions" from 'The New York Times' shown below:

1. What type of convenience store opened in Seattle on Jan. 22?

2. What details make the Amazon Go store different from a traditional grocery store?

3. What is noticeable about the photos in the article? What do they show about the new store?

4. How are items paid for in the Amazon Go store, and what is eliminated in the process?

5. What does Amazon say about the role of cashiers and potential loss of jobs with the new system? 

6. Why does the author say the experience feels like shoplifting, and what happened when he attempted to shoplift a four-pack of vanilla soda?

The above questions represent a good exercise in critical thinking for the article under scrutiny about the new grocery stores.   You may be wondering why I am bringing this up now when the stores have been open for the last few months.  The reason is that there is a larger change at hand with this new technology.  Amazon is looking to expand the information extracted about each customer by introducing new technology.  The grocery store is just one.



Inside the grocery store are a large amount of cameras which are tracking movements.  Not to scare you in any way, this is for the main purpose of tracking purchases.  Although, the amount of time that each customer stands in front of a given product is being recorded along with the customers who simply walk by and pay no attention toward a given item.  This technology is being extended into algorithms which are embedded into the 'Kindle' by Amazon.



I accidentally misplaced the reference (the name of the podcast/episode) which described the shift in Amazon's strategy to gather more information out of their readers Kindle usage.  Including tracking how long each reader stays on a page and if the reader returns to a section with a given phrase or story.  This information will inevitably help Amazon sell better books by adjusting the plot to tailor the customers exact needs.  Scary?  Possibly.

Conclusion...

The changes proposed or being sought by Amazon are interesting and potentially frightening.  As the Virtual Reality pioneer -- computer scientist -- Jaron Lanier implied in his book titled "Who Owns The Future?" -- nothing is for free in Silicon Valley.  Meaning, any discount or free technology is accompanied by a lengthy 'legal disclaimer' which is basically saying that the information collected on this device belongs to Amazon or any other technology company.



At the same time, Jaron Lanier states that in order to get around such an inevitable problem, a new system will have to arise -- something akin to 'micro-payments'.  If the user is unwilling to pay the 'micro-payment' then a short commercial might need to be watched by the user to access the 'free service'.  Ultimately, the technology offered by Amazon might not be terrible given that the time needed to search for an interesting book for a person will be reduced as A.I. algorithms become more intelligent.



In the end, the technology depends on a choice by the consumer (you and I).  Are we willing to give up our information for a "free service"?  Do we really understand what data is being collected by theses technology companies?  Do we really care what data is being collected?  These questions will have to be answered in the future as technology rapidly advances in data collection over time.



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