87 citations · 216 across the 10 of their papers we have counts for
3 papers · 1 filter
Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep Scoring
Jeroen Van Der Donckt, Jonas Van Der Donckt, Emiel Deprost +4
Over the last few years, research in automatic sleep scoring has mainly focused on developing increasingly complex deep learning architectures. However, recently these approaches a…
Deep learning models for predicting RNA degradation via dual crowdsourcing
Hannah K. Wayment-Steele, Wipapat Kladwang, Andrew M. Watkins +26
Messenger RNA-based medicines hold immense potential, as evidenced by their rapid deployment as COVID-19 vaccines. However, worldwide distribution of mRNA molecules has been limite…
GENESIM: genetic extraction of a single, interpretable model
Gilles Vandewiele, Olivier Janssens, Femke Ongenae +2
Models obtained by decision tree induction techniques excel in being interpretable.However, they can be prone to overfitting, which results in a low predictive performance. Ensembl…