Antibody responses to Borrelia burgdorferi detected by western blot vary geographically in Canada. by Nicholas H Ogden, Julie Arsenault, Todd F Hatchette, Samir Mechai, L Robbin Lindsay

“…In this study, accuracy of individual proteins of the IgG WB algorithm in predicting the overall test result in samples from Canadians was assessed. …”
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General numerical solution of integral equation for long‐range low‐frequency groundwave propagation over irregular terrain by Dan‐Dan Wang, Qi‐Zirui Lu, Chao Han, Yun Fang, Yu‐Rong Pu

“…Numerical results in two surface types, including triangular mountain and actual terrain are used to demonstrate the performance of the presented algorithm. Furthermore, it is ascertained that the non‐physical perturbations at long propagation ranges in the IE predictions are caused by the inherent uniform‐grid schemes of the numerical solution rather than the several approximations in the derivation of the IE form.…”
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Simulation of Quantum Dynamics Based on the Quantum Stochastic Differential Equation by Ming Li

“…The numerical simulation algorithm of stochastic process of direct photodetection of a driven two-level system for the predictions of the dynamical behavior is proposed. …”
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Optimization of Rituximab Therapy in Adult Patients With PLA2R1-Associated Membranous Nephropathy With Artificial Intelligence by Alexandre Destere, Maxime Teisseyre, Diane Merino, Marion Cremoni, Alexandre O Gérard, Thomas Crepin, Noémie Jourde-Chiche, Daisy Graça, Kévin Zorzi, Céline Fernandez, Vesna Brglez, Sylvia Benzaken, Vincent L.M. Esnault, Sylvain Benito, Milou-Daniel Drici, Barbara Seitz-Polski

“…We developed a machine learning algorithm to predict the risk of underdosing based on patients’ characteristics at rituximab infusion. …”
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Enhanced Convolutional Neural Network for Accurate Crop Recommendation System on Climate Data by Adnan Myasar M., AI_Sadi Hafidh l., Abhilash Pideka Kundil

“…The chosen features are classified and Improved Convolutional Neural Network (ICNN) algorithm predicts crops accurately. Our model, combining the CS-ICNN framework, offers enhanced recommendations by considering both soil-specific characteristics and environmental factors. …”
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Viscous Flow and Dynamic Stall Effects on Vertical-Axis Wind Turbines by A. Allet, I. Paraschivoiu

“…The viscous model, developed here, is used to predict aerodynamic loads and performance for the Sandia 17-m wind turbine. …”
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MEDULLARY THYROID CARCINOMA by V. S. Medvedev, P. A. Isayev, A. A. Ilyin, D. Yu. Semin, V. V. Polkin, D. N. Derbugov, S. V. Vasilkov

“…Multicenter trials are required to elaborate a diagnostic algorithm, to define treatment policy, and to predict an outcome.…”
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Harnessing gene expression to identify the genetic basis of drug resistance by Bo‐Juen Chen, Helen C Causton, Denesy Mancenido, Noel L Goddard, Ethan O Perlstein, Dana Pe'er

“…We systematically applied our algorithm to data generated from a collection of yeast segregants, using genotype and gene expression data generated under drug‐free conditions to predict the response to 94 drugs and experimentally confirmed 14 novel gene–drug interactions. …”
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Integer linear programming for unsupervised training set selection in molecular machine learning by Matthieu Haeberle, Puck van Gerwen, Ruben Laplaza, Ksenia R Briling, Jan Weinreich, Friedrich Eisenbrand, Clémence Corminboeuf

“…Within the context of physics-inspired machine learning (ML) applied to chemistry, we demonstrate the relevance of an ILP formulation to select molecular training sets for predictions of size-extensive properties. We show that our algorithm outperforms existing unsupervised training set selection approaches, especially when predicting properties of molecules larger than those present in the training set. …”
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Perceived age estimation from facial image and demographic data in young and middle-aged South Korean adults by Ilkoo Ahn, Younghwa Baek, Bok-Nam Seo, Su Eun Lim, Kyoungsik Jung, Ho Seok Kim, Jeongkyun Kim, Sukyung Lee, Siwoo Lee

“…Thus, this study aimed to propose a novel perceived age estimation algorithm to meet the need for an objective method to predict perceived age. …”
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Fuzzy logic based adaptive duty cycling for sustainability in energy harvesting sensor actor networks by Sai Krishna Mothku, Rashmi Ranjan Rout

“…In this work, current residual energy, predicted harvesting energy (for a futuristic time slot) and predicted residual energy parameters are considered as fuzzy input variables to estimate duty cycle for a sensor node. …”
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A Hybrid Deep Learning–Based Feature Selection Approach for Supporting Early Detection of Long-Term Behavioral Outcomes in Survivors of Cancer: Cross-Sectional Study by Tracy Huang, Chun-Kit Ngan, Yin Ting Cheung, Madelyn Marcotte, Benjamin Cabrera

“…ObjectiveThis study aimed to create a new feature selection algorithm to improve the performance of machine learning classifiers to predict negative long-term behavioral outcomes in survivors of cancer. …”
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Analisis Seleksi Atribut Dalam Memprediksi Kegagalan Skripsi Mahasiswa Menggunakan Algoritme Naïve Bayes pada Jurusan Sistem Informasi Universitas Brawijaya by Satrio Hadi Wijoyo, Satrio Agung Wicaksono, Admaja Dwi Herlambang

“…The highest accuracy is the Naive Bayes algorithm using data training which shows the results of 412 correct predictions with an accuracy of 82.4% and 88 false predictions with a presentation of 17.6%. …”
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A new method for surge arrester placement in high‐voltage substations considering environmental effects by Faridoddin Safaei, Mohsen Niasati

“…The lightning back flashover (BF) and switching over‐voltages are predicted with the accurate modeling of the transient behavior of all elements of high‐voltage substations and transmission lines, considering the effect of environmental conditions. …”
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METHOD FOR NUMERICAL MODELING OF UNSTEADY SEPARATED FLOW AROUND AIRFOILS MOVING CLOSE TO FLAT SCREEN by T. V. Pogrebnaya, S. D. Shipilov

“…The results of the calculations showed that at low atitudes of airfoil over screen mirror method over predicts lift force compared with movable screen, while fixed screen under predicts it. …”
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Probabilistic Solar Proxy Forecasting With Neural Network Ensembles by Joshua D. Daniell, Piyush M. Mehta

“…Currently, the USAF contracts Space Environment Technologies (SET), which uses a linear algorithm to forecast F10.7cm. In this work, we introduce methods using neural network ensembles with multi‐layer perceptrons (MLPs) and long‐short term memory (LSTMs) to improve on the SET predictions. …”
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Tree Species Classification at the Pixel Level Using Deep Learning and Multispectral Time Series in an Imbalanced Context by Florian Mouret, David Morin, Milena Planells, Cécile Vincent-Barbaroux

“…Validation on independent in situ data shows that all models struggle to predict in areas not well covered by training data, but even in this situation, the RF algorithm is largely outperformed by deep learning models for minority classes. …”
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Integrated systems biology analysis of KSHV latent infection reveals viral induction and reliance on peroxisome mediated lipid metabolism. by Zoi E Sychev, Alex Hu, Terri A DiMaio, Anthony Gitter, Nathan D Camp, William S Noble, Alejandro Wolf-Yadlin, Michael Lagunoff

“…To identify the underlying cellular mechanisms of KSHV alteration of host signaling and endothelial cell activation, we identified changes in the host proteome, phosphoproteome and transcriptome landscape following KSHV infection of endothelial cells. A Steiner forest algorithm was used to integrate the global data sets and, together with transcriptome based predicted transcription factor activity, cellular networks altered by latent KSHV were predicted. …”
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Cooperativity among short amyloid stretches in long amyloidogenic sequences. by Lele Hu, Weiren Cui, Zhisong He, Xiaohe Shi, Kaiyan Feng, Buyong Ma, Yu-Dong Cai

“…The algorithm successfully predicted and classified amyloid segments with an overall accuracy of 75%. …”
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Optimisation of Crystallisation Recipe for Varied Cloud Points Characteristics in Palm Oil Fractions by John Ting Zhi Zhang, Jeng Shiun Lim

“…The artificial neural network (ANN), which uses the Levenberg-Marquardt algorithm, serves as an internal model for predicting process output, whereas the genetic algorithm (GA) investigates a wide range of recipe combinations to maximise yield. …”
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