2.7: Conclusion

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The need and application for computational classification techniques in the medical and clinical domain are diverse, however, these systems are only as useful as their computational intelligence. Obtaining accuracies in the 70s and 80s range is a good start, but higher accuracy is needed to be an impactful industry standard. Outside of the clinical application, machine intelligence is being tested by any person with a smart phone. There is a difference between asking Siri what the symptoms of a heart attack are versus asking Siri to call emergency services because you are having a heart attack. It is possible for Siri to call emergency services for you with various commands, such as “call emergency services”, “dial 911”, or “phone 911” among others (OS X Daily), but the distinction is discrete and vital to correctly make. While it may seem small, the need for machines to understand the simple difference between phrases like “Siri, what are the symptoms of a heart attack?” and “Siri, I’m having a heart attack” are just as important as the biomedical classification techniques discussed in this paper.

All the techniques and systems reviewed are extremely important for driving efficiency and accuracy in the medical field where mistakes and oversight is rarely forgiven. By providing health care professionals with dependable, robust systems, hopefully more people can be helped, and more institutions can have systems like Watson helping them make diagnostic decisions. Big data will surely remain a buzzword for years to come but embracing the practical use of big data can be difficult. The medical field is often regarded as a groundbreaking one, but professionals in the field can be slow to embrace such advancements. Trusting computers to manage our data and help us make informed decisions lies in ensuring top results and allowing little room for error. For this reason, computational classification of biomedical and clinical concepts is a crucial foundational layer that needs to be standardized. Only when a computational system can classify data correctly, can other important results be produced from that data. Technology is ever-changing and ever- expanding, and hopefully with more advancements in computational classification techniques and achievable replication of results, more computational systems will be developed and trusted to help improve our health and save lives.