350 citations · 627 across the 3 of their papers we have counts for
3 papers
Universal Laboratory Model: prognosis of abnormal clinical outcomes based on routine tests
Pavel Karpov, Ilya Petrenkov, Ruslan Raiman
Clinical laboratory results are ubiquitous in any diagnosis making. Predicting abnormal values of not prescribed tests based on the results of performed tests looks intriguing, as…
State-of-the-Art Augmented NLP Transformer models for direct and single-step retrosynthesis
Igor V. Tetko, Pavel Karpov, Ruud Van Deursen +1
We investigated the effect of different training scenarios on predicting the (retro)synthesis of chemical compounds using a text-like representation of chemical reactions (SMILES)…
Transformer-CNN: Fast and Reliable tool for QSAR
Pavel Karpov, Guillaume Godin, Igor V. Tetko
We present SMILES-embeddings derived from the internal encoder state of a Transformer [1] model trained to canonize SMILES as a Seq2Seq problem. Using a CharNN [2] architecture upo…