Abstract: Predictive Process Monitoring (PPM) techniques leverage incomplete execution traces and historical event logs to predict outcomes, activities, and remaining time in ongoing processes.
Abstract: Predictive maintenance, utilising anomalous sound classification, demonstrates a strong potential to identify mechanical faults in industrial machinery. This research proposes a machine ...
Department of Neuroscience, The School of Translational Medicine, Monash University & Alfred Health, Melbourne, Victoria 3004, Australia Epilepsy is a dynamic, multidisciplinary field that rapidly ...
Objectives There is now good evidence that central obesity carries more health risks compared with total obesity assessed by body mass index (BMI). It has therefore been suggested that waist ...
The repository is the official implementation of the paper: "Leaderboard: Leveraging Predictive Modeling for Protein-Ligand Insights and Discovery", published in the Bioinformatics journal. The paper ...
1 Department of Computer Science, Rutgers University, New Brunswick, NJ, USA. 2 Department of Computer Science, Rochester Institute of Technology, Rochester, NY, USA. This paper presents a ...
This study introduces a sophisticated intelligent predictive maintenance system for industrial conveyor belts powered by a random forest machine learning model. The random forest model was evaluated ...
1 Pharmavite LLC, Los Angeles, CA, USA. 2 Microsoft, Charlotte, NC, USA. 3 AXS Group LLC, Los Angeles, CA, USA. 4 TCS, Indianapolis, IN, USA. Risk management is relevant for every project that which ...
We analyzed 4,427 patients with MDS divided into training and validation cohorts. Deep learning methods were applied to integrate and impute clinical/genomic features. Clustering was performed by ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results