English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

SleepioTM is a digital mobile phone and web platform that uses techniquesfrom cognitive behavioural therapy (CBT) to improve sleep in people with sleepdifficulty. As part of this process, Sleepio captures data about the sleepbehaviour of the users that have consented to such data being processed. Forneural networks, the scale of the data is an opportunity to train meaningfulmodels translatable to actual clinical practice. In collaboration with BigHealth, the therapeutics company that created and utilizes Sleepio, we haveanalysed data from a random sample of 401,174 sleep diaries and built a neuralnetwork to model sleep behaviour and sleep quality of each individual in apersonalised manner. We demonstrate that this neural network is more accuratethan standard statistical methods in predicting the sleep quality of anindividual based on his/her behaviour from the last 10 days. We compare modelperformance in a wide range of hyperparameter settings representing variousscenarios. We further show that the neural network can be used to producepersonalised recommendations of what sleep habits users should follow tomaximise sleep quality, and show that these recommendations are substantiallybetter than the ones generated by standard methods. We finally show that theneural network can explain the recommendation given to each participant andcalculate confidence intervals for each prediction, all of which are essentialfor clinicians to be able to adopt such a tool in clinical practice.

Personalised recommendations of sleep behaviour with neural networks using sleep diaries captured in Sleepio