Sensors Expo & Conference 2018: Predictive Analysis The Critical Link For Bio Sensing | Sensors Magazine
Bio sensing has matured nicely. Medical professionals, forensics experts, law enforcement, and other users can gather mass quantities of physiological data, from vital signs to DNA markers using bio sensors and related interfaces, hardware, and software. However, like any ‘big data’ collection, the hard part is weeding through all that data and making some kind of a deduction or conclusion on the subject under test.
For example, if we are looking for the source of piloerections in a particular mammal, our sensors collect a plethora of data, recording nearly every physical response to test stimuli during a set time period. How do we decipher which data is relevant to piloerections? It all could be important, or perhaps just a few parameters or even none. How would we know? Enter Arvind Ananthan.
Arvind Ananthan is the Global Business Development Manager, Medical Devices & Healthcare at MathWorks and he will be addressing this very topic at Sensors Expo & Conference 2018, Wednesday June 27, 2018 from 3:30 PM to 4:20 PM. Proliferation of low-cost/high-fidelity biomedical sensors and wearable devices has enabled us to acquire vast amounts of physiological signals; however, developing predictive analytics using machine learning algorithms to effectively analyze this trove of information has been a challenging task. In his talk, Mr. Ananthan will look at a realistic problem such as ECG signal classification or automated medical image (MRI) segmentation to explore the newer advanced machine learning and deep learning workflows that is poised to revolutionize this segment.