10. Healthcare Goes Digital
“Healthcare is way behind. But there’s an
amazing awakening and the future is very
promising in terms of internet connectivity and
using big data to predict diseases before they
even happen.” - See more at:
「predict = 予測」 は 機械学習がマッチする
19. [事例] Halo 4 on Xbox ゲーム分析
On Premises SQL Server Azure Blob Storage
1000’s Log FilesNew User View
Copy NewUsers to
Azure Data Factory
Mask & Geo-
30. Microsoft Has Health Care Hopes With Revolution Analytics Buy
As their volumes of data continually
grow, organizations of all kinds
around the world – financial,
manufacturing, health care, retail,
research – need powerful analytical
models to make data-driven
This requires high performance
computation that is “close” to the
data, and scales with the business’
needs over time. At the same time,
companies need to reduce the data
science and analytics skills gap
inside their organizations, so more
employees can use and benefit from
32. • Through the creation of new applications and
platforms, our team works to accelerate the rate
of research in areas such as machine learning and
computer vision making it easier for scientists to
access large test datasets and compare algorithms
against common benchmarks. In collaboration with
clinicians, we are working towards the goal of
making medical images understandable to a
• We work with top research institutes around the
world to make data and tools available and
advance the state of the art in automatic analysis
of medical scans.
Medical Imaging at Microsoft Research
33. •Volume dimensions and Voxel Spacing are displayed on the top.
•Settings for the segmentation computation is on the left under Settings.
•All three views are interactive. Swap any secondary view with the main
workspace by clicking on the arrow on the top left.
GeoS for the assisted segmentation of 3-D medical scans
A very easy-to-use, free Windows application for the segmentation of
anatomical regions within 2-D and 3-D medical images, such as CT, X-ray,
and MR scans
Brush Strokes Added
34. CodaLab is an open source platform that enables researchers to
rigorously compare the accuracy of image analysis algorithms with
respect to one another.
Define the problem as a binary classification problem
Identify population based on playing start date and duration
Looking at the next 7 days as source for labeling
If the user plays less than x game sessions during this period, we consider her churned
Use a week worth of data for training and testing
Using Boosted Decision Tree as the base algorithm for training/prediction
32 Max leaves per tree
Advanced analytics is using products like Azure Machine Learning to find new and actionable insights that traditional approaches to business intelligence are unlikely to discover. Today when confined by only BI tools without a connection to machine learning, it is solely the job of the human looking at the spreadsheet to gain insights and react to the data. But a human can only consume so many variables. A computer, on the other hand, can consume a great deal more variables to provide much deeper insight on the data. This is why we say beyond business intelligence – It’s machine intelligence.
We have 4 advantages in Azure ML.
You can get started with just a browser. With only an Azure subscription, you can take advantage of the full functionality of Azure Machine Learning within minutes.
Another limit with other machine learning solutions are siloed environments that only allow for one programming language or make changing from one algorithm to another time consuming and complex. With Azure ML, you can experience the power of choice. That choice expands to language, with both Python and R being first class citizens of Azure ML, or algorithm. You can choose from hundreds of algorithms, including business-tested ones running our Microsoft businesses today.
Most revolutionary of all you can deploy solutions in minutes as a web service, which is simply a url which can connect to any data, anywhere – including on-premises or in another cloud environment. The ability to put a model into production almost immediately, as well as revise it easily, is unique to Microsoft and allows companies to stay on top of the changing business landscape more effectively than is offered by any other provider today.
We even take that a step further, allowing model developers to connect to the world with our Machine Learning Marketplace, where they can publish finished solutions and APIs with their own brand and business model. Check it out at https://datamarket.azure.com/.
GA in February this year.