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Update on Physionet 2017

A project log for Early and low cost detection of Heart Failure

Heart Failure is a debilitating condition that most old people encounters. A PoC uses coded signals, Doppler and a sound ML classifier.

Jean Pierre Le RouzicJean Pierre Le Rouzic 01/25/2018 at 11:120 Comments

Unfortunately I did not attend the Physionet conference even if it was in my home town, participants have to pay an entrance price, and for an individual it is just impossible.

The competition was about: AF Classification from a short single lead ECG recording.

75 International teams competed. It was not about heart sounds as in 2016, but given the high number of heart beats detectors in HaD, many people should be interested in this competition.

What technology did dominated the competition, well most ML classifiers en vogue at the moment: Deep forest, XGBoost. A lot of teams used LASSO for feature selection.

It can be seen as a success for ML, as it succeeds with far much less data than a practitioner access in a single day

However Gari Clifford tells that there are signs of over training in the competition submissions (the model fits the data in a way that should not be expected if samples were distributed at random).

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