Demonstrate an understanding of the background and context of the project. Justify the approach you used. Describe the equipment and/or software tools used. describe the main outcomes and place them in context.
Research attempting to identify people at risk for AF have focused on finding features in the electrical signal of the heart (measured through an electrocardiogram or ECG) that can predict the likelihood of an individual suffering from AF in the future. These works have low sensitivity, possibly due to only paying attention to specific segments of the ECG, ignoring most of the data that is collected. This project will develop a machine learning algorithm to predict AF onset using the entire ECG signal‘s features and compare its sensitivity to current state-of-the art prediction algorithms.
regards to the osmosis of pieces into lumps. Mill operator recognizes pieces and lumps of data, the differentiation being that a piece is comprised of various pieces of data. It is fascinating to take note of that while there is a limited ability to recall lumps of data, how much pieces in every one of those lumps can change broadly (Miller, 1956). Anyway it’s anything but a straightforward instance of having the memorable option huge pieces right away, somewhat that as each piece turns out to be more natural, it very well may be acclimatized into a lump, which is then recollected itself. Recoding is the interaction by which individual pieces are ‘recoded’ and allocated to lumps. Consequently the ends that can be drawn from Miller’s unique work is that, while there is an acknowledged breaking point to the quantity of pieces of data that can be put away in prompt (present moment) memory, how much data inside every one of those lumps can be very high, without unfavorably influencing the review of similar number