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Machine learning (ML) provides an efficient method to predict the unknown properties during the exploration of new materials, but how to efficiently represent the molecules as input is still not fully solved. Inspired by image processing, one of the classical ML tasks, this work developed a method to predict the structure‐dependent properties by converting the atom position into a three‐dimensional...
Objective
To apply unsupervised machine learning to patient‐reported outcomes to identify clusters of epilepsy patients exhibiting unique psychosocial characteristics.
Methods
Consecutive outpatients seen at the Calgary Comprehensive Epilepsy Program outpatient clinics with complete patient‐reported outcome measures on quality of life, health state valuation, depression, and epilepsy severity and...
The NAGLU challenge of the fourth edition of the Critical Assessment of Genome Interpretation experiment (CAGI4) in 2016, invited participants to predict the impact of variants of unknown significance (VUS) on the enzymatic activity of the lysosomal hydrolase α‐N‐acetylglucosaminidase (NAGLU). Deficiencies in NAGLU activity lead to a rare, monogenic, recessive lysosomal storage disorder, Sanfilippo...
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