3 Use Cases for AI, Machine Learning and Deep Learning: Healthcare, Digitization and Proactive Support
For us in the Boston area, we watched our Red Sox end their record-setting season by celebrating another World Series title.
Naturally, there has been much buzz about the team, as well as first-year manager Alex Cora and the clubhouse culture he built. However, it takes more than culture change to win, and Cora and the Red Sox front office recognize that. We live in a data-driven world, and that includes the world of baseball.
A recent Boston Globe story featured a good example of how the Red Sox use data-driven insights to make in-game decisions. It isn’t luck when outfielder Mookie Betts snags a fly ball that most observers would think he had no chance to catch. What places Betts in the ideal position is data, retrieved through AI and analytics that captures and analyzes the batter’s historical and future trends. The output of that learning is placed on an index card which Betts keeps in his back pocket, so he can move to the optimal position in the field before each at-bat.
Perhaps a Red Sox legend like Ted Williams would dismiss today’s approach to analyzing the other team. However, the data has always been there. Today’s difference is the availability of intelligent analysis through AI and Machine Learning. Modern tools to provide managers a modern twist to strategy.
Whether baseball or the business world, organizations are collecting vast amounts of new data points and racing to unlock its value to help make faster and better decisions.
At Dell Technologies, we help our customers deliver new outcomes through AI and ML. At the same time, we as a company are doing what our customers are doing – leveraging AI and ML to help us make better decisions and improve customer experiences and outcomes.
Before proudly sharing a few examples, I invite you to check out Dell Technologies “Unlock the Power of Data,” which was streamed as a virtual event for customers and partners on November 14. During the broadcast, trends in AI were discussed, use cases and examples outlined, and Dell Technologies AI capabilities demonstrated.
Delivering Targeted Healthcare Insights with AI and Machine Learning
The medical industry is well-positioned to be a top benefactor of the AI/ML evolution, enabling providers to better evaluate patients and personalize treatment options.
In this case, a regional healthcare provider partnered with Dell EMC Consulting to develop and implement a robust analytics research platform that would enable an extensive community of researchers and innovators to work more efficiently with faster and expanded access to critical data.
One such example is a recent collaboration between the healthcare provider’s data scientists and data scientists from Dell EMC Consulting. The teams together delivered new research targeted at the alarmingly high number of seizures that occur in hospitals, most of which are only detectable by brain monitoring with an electroencephalogram (EEG). Delayed diagnosis of such “subclinical seizures” leads to brain damage, lengthens hospitalization, and heightens the risk of in-hospital death or long-term disability.
The learnings from past EEGs would go a long way towards helping hospital physicians provide better diagnosis and treatment. However, there are two key challenges that make curating and mining the information difficult. First, patients’ EEG reports and the corresponding waveform data files are often stored separately and not clearly linked. Equally challenging is the ability to quickly extract useful information from the reports that describe clinically important neurophysiological events.
Using the new research platform and applying advanced AI and machine learning techniques, the joint team developed a highly accurate classifier for pairing the report files with the corresponding data. They also discovered several analysis techniques that are highly accurate in extracting the relevant information needed from the reports. With these two foundations, the team has established a highly effective and efficient data pipeline for clinical operations, quality improvement, and neurophysiological research.
Using Machine Learning to Automate the Offline
Dell’s eCommerce platform is the front door for the full range of customer inquiries from simple browsing to real-time support. However, did you know that Dell manages more than four million offline orders that arrive via fax and email each year? Our global Order Management and Support organization has traditionally executed those orders manually. However, a new solution was needed to improve order accuracy and cycle time.
Leveraging machine learning and the latest in Optical Character Recognition (OCR), Dell Digital developed Robotix — a scalable solution for digitizing offline purchase orders. Robotix improves the customer experience by processing orders faster and reducing pain points, while automating offline quality checks and customizing order entry instructions.
Robotix, currently patent-pending, is already live in North America and expected to automate the majority of global offline orders in its first full year of implementation.
Proactively Avoiding System Failure with SupportAssist
The millions of customer systems connected to Dell EMC around the globe can run trillions of variations of hardware and software configurations. These variations may be further influenced by factors such as geographic location and climate.
Given such a vast scope and size, the ability to predict and validate potential faults may seem like an impossible task. However, through the power of AI and ML, and the capacity of today’s Graphics Processing Units, our internal data scientists have built solutions that implement Deep Learning models to open a world of even more possibilities.
Today, SupportAssist, our automated proactive and predictive technology, is run on almost 50 million customer systems. Through this connected technology, Dell EMC can save customers from the potentially disastrous impact of downtime or data loss by alerting and remediating a potential hard drive failure on average 50 days before the failure occurs. And as our services technology continues to get smarter, customers will be empowered to make faster, better decisions about their IT, and address immediate issues while they plan for what’s next.
These are just a few of the many, many AI/ML use cases deployed either internally by Dell Technologies or externally by our customers. Yet, while implementations vary, there is a common thread tying them together that equates to success. The right people and processes, combined with these powerful technologies, that enable us to define and execute a vision that brings data and insights to life and makes transformation real.