Links for time series forecast

HMM API in python (seqlearn):

• http://larsmans.github.io/seqlearn/reference.html#module-seqlearn.hmm

General

• https://machinelearningmastery.com/time-series-forecasting-methods-in-python-cheat-sheet/
• https://machinelearningmastery.com/introduction-to-time-series-forecasting-with-python/
• https://machinelearningmastery.com/taxonomy-of-time-series-forecasting-problems/
• https://medium.com/open-machine-learning-course/open-machine-learning-course-topic-9-time-series-analysis-in-python-a270cb05e0b3
• https://medium.com/open-machine-learning-course/open-machine-learning-course-topic-9-time-series-analysis-in-python-a270cb05e0b3

Using statistical methods

• https://people.duke.edu/~rnau/411home.htm
• http://www.blackarbs.com/blog/time-series-analysis-in-python-linear-models-to-garch/11/1/2016

Using classical ML:

using DL:

• https://machinelearningmastery.com/time-series-prediction-lstm-recurrent-neural-networks-python-keras/
• https://mapr.com/blog/deep-learning-tensorflow/
• http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0180944&type=printable
• Deep Learning Networks for Stock Market Analysis and Prediction: Methodology, Data Representations, and Case Studies http://dro.dur.ac.uk/21533/1/21533.pdf
• https://ccc.inaoep.mx/~pgomez/conferences/PggISCI14.pdf
• https://medium.com/machine-learning-world/neural-networks-for-algorithmic-trading-2-1-multivariate-time-series-ab016ce70f57

Predicting time-series of EHR/ data-mining of time series of EHR

• https://www.nature.com/articles/s41746-018-0029-1.pdf: this one might be really relevant for my problem
• https://www.nature.com/articles/s41598-018-24271-9.pdf: very relevant as well: uses GRUs.
• https://ac.els-cdn.com/S1532046416301654/1-s2.0-S1532046416301654-main.pdf?_tid=4b9d712d-66cb-40c6-b4aa-e7abb0f9ec37&acdnat=1533922921_8242ea50b0e5c95f1d6d252adfbaa7a7
• https://reader.elsevier.com/reader/sd/FD9B54351953FD9427CDE8600FE2BC355505A01313FBC234CEB086D7E38D85592813179D5043FC287D7E355CF82CB114
• DEEP PATIENT: https://www.nature.com/articles/srep26094.pdf

Using DL Methods:

• https://arxiv.org/pdf/1706.03446.pdf: TO READ IN PRIORITY: all the DL Methods for EHR problems.
• https://arxiv.org/pdf/1807.01705.pdf: use transfer learning from the MIMIC database to predict time series of EHR.