How Artificial Intelligence is Revolutionizing Personalized Medicine

 
Uncategorized

Imagine becoming gravely ill and yet being able to receive an accurate diagnosis with a recommended treatment plan in just 10 minutes. Sound like the future? This is actually happening now with the help of Artificial Intelligence (AI).  The University of Tokyo recently reported that Watson, IBM’s cognitive supercomputer, correctly diagnosed a rare form of leukemia in a 60-year-old woman. Doctors originally thought the woman had acute myeloid leukemia, but after examining 20 million cancer research papers in 10 minutes, Watson was able to correctly determine the actual disease and recommend a personalized treatment plan.  AI – and its related applications, Machine Learning (ML) and Deep Learning (DL) – are changing healthcare as we know it. The advancements made in AI will revolutionize research and, ultimately, personalized medicine.

The Historical Challenge with Data

Big Data has been a buzz word for several years now. Hospitals, like enterprises, have been drowning in big data. From the moment doctors begin keeping patient records, they – and now hospitals – have been amassing large quantities of complex data within patient medical records; including handwritten notes, X-ray results, blood samples, vital signs, DNA sequences, and more. Historically, this data has been disparate and existed in hard copies only, making it nearly impossible to analyze in aggregate. Now with AI, analytic tools and other technological advancements, there is a way to actually organize, analyze and cross reference the data, enabling hospitals, doctors and researchers to finally put that data to use. With medical devices alone, the influx of data is staggering, necessitating that hospitals – and the medical industry in general – rethink the way they collect, store and analyze data.

AI Revolutionizes Personalized Medicine  

While there is generally a solution to any problem, often times it isn’t that we can’t see the solution, it’s that we can’t correctly identify the problem. AI is able to learn from each piece of data it is given and rapidly re-evaluate its analysis as more data and more is received. This enables doctors and researchers to better identify problems and, subsequently, the potential solutions to those problems. A door to a world of possibilities has now been opened, and with it, the potential to find cures for the thus-far incurable diseases, perhaps even within our lifetime.

AI is not limited to traditional data on a spread sheet. It can interpret and aggregate imaging, text, handwritten notes, test results, sensor data, and even demographic and geo-spatial data. AI will be able to cross reference data, find commonalities and draw insights that were previously impossible due to data silos or the sheer amount of time it would take for a human to crunch the numbers. It can also consider seemingly unrelated or outside factors that doctors and researchers may not immediate see as relevant. For example, environmental factor, such as elevation, humidity and proximity to certain dense mineral deposits, factories or agriculture. This ability to rapidly analyze data, and potential correlations, creates a more comprehensive and holistic view into a patient’s health.

AI in Action Today

  • The National Cancer Institute has partnered with NVIDIA to develop an AI framework – powered by Mellanox InfiniBand adapters and aimed at supercharging cancer research. The framework, CANDLE (Cancer Distributed Learning Environment), will leverage AI to extract and study millions of patient records with the goal of understanding how cancer spreads and reoccurs. This is an example of AI being able to pour through large amounts of genomic data in a quick manner so doctors can draw conclusions.
  • A recent study published in Neurobiology of Aging found that AI could help detect signs of Alzheimer’s in patient brain scans before doctors. AI is currently being used to study scans of healthy brains and brains affected by Alzheimer’s to learn and identify the telling systems of the disease.
  • Medecision, a leading global healthcare information technology provider, is also employing AI to sweep through large amounts of data, identifying variables and predicting avoidable hospitalizations in diabetes patients. The medical community has only just begun to scratch the surface of what can be achieved with AI.

Preparing for Impact

AI is impacting nearly every aspect of the healthcare industry from patient care such as the examples described herein to hospital security and pharmaceutical drug development (stay tuned for a future post on how AI may just be the solution to rising drug prices). Mellanox is committed to the cause and is helping to accelerate many of the world’s leading AI, ML and DL systems with solutions like RDMA, GPUDirect RDMA, SHARP and intelligent interconnects that are able to handle the highest rates of real-time data and mitigate network congestion. We have only just begun to scratch the surface of AI’s potential and Mellanox believes that AI has the potential to improve our quality of life, find cures for life’s most threating illnesses and provide a deeper understanding of our own evolution.

About Scot Schultz

Scot Schultz is a HPC technology specialist with broad knowledge in operating systems, high speed interconnects and processor technologies. Joining the Mellanox team in March 2013 as Director of HPC and Technical Computing, Schultz is a 25-year veteran of the computing industry. Prior to joining Mellanox, he spent the past 17 years at AMD in various engineering and leadership roles, most recently in strategic HPC technology ecosystem enablement. Scot was also instrumental with the growth and development of the Open Fabrics Alliance as co-chair of the board of directors. Scot currently maintains his role as Director of Educational Outreach, founding member of the HPC Advisory Council and of various other industry organizations. Follow him on Twitter: @ScotSchultz

Comments are closed.