Artificial intelligence (AI) and machine learning (ML) are two topics that have been gaining substantial traction in recent years; we are periodically hearing a lot about the latest advancements in AI and ML although just taking the initial steps in this field. Imagine what will happen when these innovations are merged with other promising tech, such as big data. This article, written by MetaOptima’s Big Data Engineer, Ramaninder Singh, provides insight into how the latest AI and ML technologies will develop, merge, and revolutionize the healthcare sector.
“We don’t have better algorithms. We just have more data.” - Peter Norvig, Google’s Research Director on the power of dataIntroduction
As we know, big data is the huge amount of data which we as a society collect exponentially with every passing day. To provide insight into just how vast this bank is, the amount of data created from the beginning of recorded time up to the year 2000 is roughly equivalent to the sum we are now creating every 2-3 days!1
In this digital world, data is coming at us from every direction; it becomes challenging to find meaning within the overwhelming amount of information. Major benefactors of this data include the field of artificial intelligence (AI) and machine learning (ML). Therefore, it is essential that the power of big data be unlocked to develop the best results that these technologies can offer.
The availability of big data has fostered unprecedented breakthroughs in artificial intelligence (AI) and machine learning (ML) that could not have been possible before. In order for machine learning algorithms to become smarter with time, they require access to large quantities of data to continue their “learning” process.
As the quantity of data increases, this provides greater opportunity for the machine learning and artificial intelligence algorithms to find patterns and associations in the data. In a cyclical manner, as more patterns and associations are located it further improves the accuracy of predictions made by the algorithms from data they foresee developing. In this way, artificial intelligence (AI) and machine learning (ML) systems are like humans; the more experience a computer has (with information provided by big data), the better the results will be.Big Data In Healthcare
When combined with big data, artificial intelligence (AI) and machine learning (ML) can create impacting, long-lasting value in a wide variety of fields such as healthcare. For example, countries such as the United States are currently facing a shortage of physicians and dermatologists.2
Intelligent dermatology software such as DermEngine’s Visual Search utilizes advanced clinical decision support tools powered by deep learning to provide medical experts with deep insights on visually similar images to a submitted patient image. This is an excellent educational resource that supports dermatologists in their practice through providing top diagnoses and risk of malignancy of visually similar cases using content-based image retrieval algorithms (CBIR).
It is argued by some that as machine learning and artificial intelligence continue to grow with the intrinsic increase in amount of big data in healthcare, predictive analytics will become a standard tool. Although not considered predictive analytics due to its educational purposes, it is easy to see how tools like Visual Search are leading the way in supporting physicians with valuable data to support clinical decisions.
Combining human and artificial intelligence with the power of big data is a valuable tool towards developing innovative, and revolutionary insights that can re-shape how healthcare is provided. As previously discussed, large quantities of quality data are essential to providing powerful machine learning outcomes. As the amount of data and cross-platform communication (interoperability) increases, healthcare will be substantially impacted by a wave of intrinsic, meaningful insights.