Computational models for the classification of mPGES-1 inhibitors with fingerprint descriptors
Sign Up to like & getrecommendations! Published in 2017 at "Molecular Diversity"
DOI: 10.1007/s11030-017-9743-x
Abstract: Human microsomal prostaglandin $$\hbox {E}_{2}$$E2 synthase (mPGES)-1 is a promising drug target for inflammation and other diseases with inflammatory symptoms. In this work, we built classification models which were able to classify mPGES-1 inhibitors into… read more here.
Keywords: fingerprint descriptors; classification; test set; mpges inhibitors ... See more keywords
Discrimination of mining microseismic events and blasts using convolutional neural networks and original waveform
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Central South University"
DOI: 10.1007/s11771-020-4530-8
Abstract: Microseismic monitoring system is one of the effective methods for deep mining geo-stress monitoring. The principle of microseismic monitoring system is to analyze the mechanical parameters contained in microseismic events for providing accurate information of… read more here.
Keywords: test set; microseismic events; convolutional neural; microseismic monitoring ... See more keywords
Deep Learning for the Detection of Breast Cancers on Chest Computed Tomography.
Sign Up to like & getrecommendations! Published in 2021 at "Clinical breast cancer"
DOI: 10.1016/j.clbc.2021.04.015
Abstract: BACKGROUND Incidental breast cancers can be detected on chest computed tomography (CT) scans. With the use of deep learning, the sensitivity of incidental breast cancer detection on chest CT would improve. This study aimed to… read more here.
Keywords: breast; test set; deep learning; case ... See more keywords
Prediction of chemical toxicity to Tetrahymena pyriformis with four-descriptor models.
Sign Up to like & getrecommendations! Published in 2020 at "Ecotoxicology and environmental safety"
DOI: 10.1016/j.ecoenv.2019.110146
Abstract: A quantitative structure-toxicity relationship (QSTR) model based on four descriptors was successfully developed for 1163 chemical toxicants against Tetrahymena pyriformis by applying general regression neural network (GRNN). The training set consisting of 600 organic compounds… read more here.
Keywords: tetrahymena pyriformis; test set; grnn model; toxicity ... See more keywords
Improving the Efficiency of Beyond-RPA Methods within the Dielectric Matrix Formulation: Algorithms and Applications to the A24 and S22 Test Sets.
Sign Up to like & getrecommendations! Published in 2017 at "Journal of chemical theory and computation"
DOI: 10.1021/acs.jctc.7b00837
Abstract: Within a formalism based on dielectric matrices, the electron-hole time-dependent Hartree-Fock (eh-TDHF) and the adiabatic connection second-order screened exchange (AC-SOSEX) are promising approximations to improve ground-state correlation energies by including exchange effects beyond the random… read more here.
Keywords: test set; matrix; s22 test; test ... See more keywords
Koopmans-Compliant Functionals and Potentials and Their Application to the GW100 Test Set.
Sign Up to like & getrecommendations! Published in 2019 at "Journal of chemical theory and computation"
DOI: 10.1021/acs.jctc.8b00976
Abstract: Koopmans-compliant (KC) functionals have been shown to provide accurate spectral properties through a generalized condition of piecewise linearity of the total energy as a function of the fractional addition/removal of an electron to/from any orbital.… read more here.
Keywords: test set; gw100 test; koopmans compliant; compliant functionals ... See more keywords
Main-group test set for materials science and engineering with user-friendly graphical tools for error analysis: systematic benchmark of the numerical and intrinsic errors in state-of-the-art electronic-structure approximations
Sign Up to like & getrecommendations! Published in 2019 at "New Journal of Physics"
DOI: 10.1088/1367-2630/aaf751
Abstract: Understanding the applicability and limitations of electronic-structure methods needs careful and efficient comparison with accurate reference data. Knowledge of the quality and errors of electronic-structure calculations is crucial to advanced method development, high-throughput computations and… read more here.
Keywords: group test; test set; electronic structure; main group ... See more keywords
AI FOR AF IN ASIANS-WHERE ARE WE AND WHERE RE WE GOING?
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Hypertension"
DOI: 10.1097/01.hjh.0000835928.48969.58
Abstract: Objective: We aimed to construct a random forest model to predict atrial fibrillation (AF) in Chinese population. Design and method: This study was comprised of 682 237 subjects with or without AF. Each subject had… read more here.
Keywords: prediction model; asians going; test set; prediction ... See more keywords
Prediction of Bone Marrow Biopsy Results From MRI in Multiple Myeloma Patients Using Deep Learning and Radiomics.
Sign Up to like & getrecommendations! Published in 2023 at "Investigative radiology"
DOI: 10.1097/rli.0000000000000986
Abstract: OBJECTIVES In multiple myeloma and its precursor stages, plasma cell infiltration (PCI) and cytogenetic aberrations are important for staging, risk stratification, and response assessment. However, invasive bone marrow (BM) biopsies cannot be performed frequently and… read more here.
Keywords: bone marrow; test set; test; cytogenetic aberrations ... See more keywords
Functionally Possible Scan-Based Test Set as a Dual of a Compressed Multicycle Test Set
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems"
DOI: 10.1109/tcad.2022.3193902
Abstract: Functionally possible scan-based tests create functional operation conditions during their functional capture cycles. This is important for avoiding failures that are caused by nonfunctional operation conditions rather than faults. However, the fault coverage achievable by… read more here.
Keywords: possible scan; test set; based test; test ... See more keywords
Automated Epilepsy Diagnosis Using EEG With Test Set Evaluation
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Neural Systems and Rehabilitation Engineering"
DOI: 10.1109/tnsre.2019.2914603
Abstract: Several electroencephalogram (EEG)-based predictive models for automated epilepsy diagnosis have been proposed over more than a decade. However, to the best of our knowledge, none have been evaluated on a holdout/test set. A vast majority… read more here.
Keywords: diagnosis; set evaluation; automated epilepsy; epilepsy diagnosis ... See more keywords