Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing machine learning models that can achieve this on the ...
Recently, utilization of Machine Learning (ML) has led to astonishing progress in computational protein design, bringing into reach the targeted engineering of proteins for industrial and biomedical applications. However, the design of proteins for emerg
As compared to conventional biomarkers, machine learning algorithms can learn nonlinear and complex interactions and thus improve prediction accuracy. This study aimed at evaluating role of biochemical and immunological parameters鈥揵ased machine learning algorithms for severity indexing in COVID19. Methods...
Therefore, this work proposes a machine learning-based method for optimizing beam pair selection and its update time. The method is structured around three main modules: spatial characterization of beam pair service areas, training of a machine learning model using collected beam pair data, and an...
Therefore, machine learning is often utilized by SHM to enhance the capabilities of the monitoring systems. In this paper, an ML aided real-time NDE and a FRP design using principal component analysis (PCA) and ANN are proposed to handle the uncountable variables of carbon–aramid hybrid fibers...
Li D. Machine learning aided decision making and adaptive stochastic control in a hierarchical interactive smart grid. Dissertations & theses - gradworks; ... D Li - The University of New Mexico. 被引量: 0发表: 2014年 Machine-Learning Aided Optimal Customer Decisions for an Interactive Smart Gr...
The work includes building of an online testing platform and developing framewo…" [more]doi:10.1007/978-1-4419-1428-6_4252Antonella GasbarriCarlos TomazChristine D. TsangRobert J. BarryDaniel Grollman
His Ph.D. from the Uni-versity of Michigan was on “spell check for radiologists,” a computer-aided diagnosis system for estimating malignancy on thoracic CT scans. Emmanuel Bertrand is a senior program manager on the Azure IoT Edge team, where he...
We have demonstrated a machine learning-aided approach to the design of mycotoxin detoxifiers (MDTs). We used a dataset of experimental in vitro assessment of the adsorption and efficiency of various MDTs against regulated mycotoxins (DON, T2, ZEN, OTA, FB1, AFB1) to build two random forest...
Here, we use a structure-based, machine learning algorithm to engineer a robust and active PET hydrolase. Our mutant and scaffold combination (FAST-PETase: functional, active, stable and tolerant PETase) contains five mutations compared to wild-type PETase (N233K/R224Q/S121E from prediction ...