Machine learned metaheuristic optimization of the bulk heterojunction morphology in P3HT:PCBM thin films
Sign Up to like & getrecommendations! Published in 2021 at "Computational Materials Science"
DOI: 10.1016/j.commatsci.2020.110119
Abstract: Abstract We discuss results from a machine learned (ML) metaheuristic cuckoo search (CS) optimization technique that is coupled with coarse-grained molecular dynamics (CGMD) simulations to solve a materials and processing design problem for organic photovoltaic… read more here.
Keywords: machine learned; morphology; pcbm; optimization ... See more keywords
Machine-learned cluster identification in high-dimensional data
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Biomedical Informatics"
DOI: 10.1016/j.jbi.2016.12.011
Abstract: Graphical abstract 3-D representation of high dimensional data following ESOM projection and visualization of group (cluster) structures using the U-matrix, which employs a geographical map analogy of valleys where members of the same cluster are… read more here.
Keywords: high dimensional; learned cluster; machine learned; dimensional data ... See more keywords
Machine learned hybrid Gaussian analysis of COVID-19 pandemic in India
Sign Up to like & getrecommendations! Published in 2021 at "Results in Physics"
DOI: 10.1016/j.rinp.2021.104630
Abstract: This article discusses short term forecasting of the Novel Corona Virus (COVID -19) data for infected, recovered and active cases using the Machine learned hybrid Gaussian and ARIMA method for the spread in India. The… read more here.
Keywords: learned hybrid; machine learned; covid; india ... See more keywords
Machine-learned metrics for predicting the likelihood of success in materials discovery
Sign Up to like & getrecommendations! Published in 2020 at "npj Computational Materials"
DOI: 10.1038/s41524-020-00401-8
Abstract: Materials discovery is often compared to the challenge of finding a needle in a haystack. While much work has focused on accurately predicting the properties of candidate materials with machine learning (ML), which amounts to… read more here.
Keywords: machine; machine learned; likelihood; materials discovery ... See more keywords
Regio-selectivity prediction with a machine-learned reaction representation and on-the-fly quantum mechanical descriptors†
Sign Up to like & getrecommendations! Published in 2020 at "Chemical Science"
DOI: 10.1039/d0sc04823b
Abstract: Accurate and rapid evaluation of whether substrates can undergo the desired the transformation is crucial and challenging for both human knowledge and computer predictions. Despite the potential of machine learning in predicting chemical reactivity such… read more here.
Keywords: machine learned; regio selectivity; reaction; learned reaction ... See more keywords
Exploring the configurational space of amorphous graphene with machine-learned atomic energies
Sign Up to like & getrecommendations! Published in 2022 at "Chemical Science"
DOI: 10.1039/d2sc04326b
Abstract: Two-dimensionally extended amorphous carbon (“amorphous graphene”) is a prototype system for disorder in 2D, showing a rich and complex configurational space that is yet to be fully understood. Here we explore the nature of amorphous… read more here.
Keywords: configurational space; machine learned; atomic energies; amorphous graphene ... See more keywords
How fast do defects migrate in halide perovskites: insights from on-the-fly machine-learned force fields.
Sign Up to like & getrecommendations! Published in 2023 at "Chemical communications"
DOI: 10.1039/d3cc00953j
Abstract: The migration of defects plays an important role in the stability of halide perovskites. It is challenging to study defect migration with experiments or conventional computer simulations. The former lacks an atomic-scale resolution and the… read more here.
Keywords: force fields; halide perovskites; defects migrate; machine learned ... See more keywords
0435 Machine-learned combination of ventilatory, hypoxic, and arousal burdens classifies daytime sleepiness better than AHI
Sign Up to like & getrecommendations! Published in 2023 at "SLEEP"
DOI: 10.1093/sleep/zsad077.0435
Abstract: The apnea-hypopnea index (AHI), the current severity metric used clinically for diagnosing obstructive sleep apnea (OSA), does not correlate well to daytime sleepiness measured via the Epworth Sleepiness Scale (ESS). Here, we assessed whether a… read more here.
Keywords: ventilatory hypoxic; learned combination; ventilatory; daytime sleepiness ... See more keywords
Psychological Measurement in the Information Age: Machine-Learned Computational Models
Sign Up to like & getrecommendations! Published in 2022 at "Current Directions in Psychological Science"
DOI: 10.1177/09637214211056906
Abstract: Psychological science can benefit from and contribute to emerging approaches from the computing and information sciences driven by the availability of real-world data and advances in sensing and computing. We focus on one such approach,… read more here.
Keywords: information; computational models; machine learned; psychology ... See more keywords
Non-standard trajectories found by machine learning for evaporative cooling of 87Rb atoms.
Sign Up to like & getrecommendations! Published in 2019 at "Optics express"
DOI: 10.1364/oe.27.020435
Abstract: We present a machine-learning experiment involving evaporative cooling of gaseous 87Rb atoms. The evaporation trajectory was optimized to maximize the number of atoms cooled down to a Bose-Einstein condensate using Bayesian optimization. After 300 trials… read more here.
Keywords: evaporative cooling; non standard; machine; machine learned ... See more keywords
Development and validation of a machine learned algorithm to IDENTIFY functionally significant coronary artery disease
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Cardiovascular Medicine"
DOI: 10.3389/fcvm.2022.956147
Abstract: Introduction Multiple trials have demonstrated broad performance ranges for tests attempting to detect coronary artery disease. The most common test, SPECT, requires capital-intensive equipment, the use of radionuclides, induction of stress, and time off work… read more here.
Keywords: disease; coronary artery; artery disease; machine learned ... See more keywords