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Decoding the JAK-STAT Axis in Colorectal Cancer with AI-HOPE-JAK-STAT: A Conversational Artificial Intelligence Approach to Clinical–Genomic Integration by Yang, Ei-Wen, Waldrup, Brigette, Velazquez-Villarreal, Enrique

“…: AI-HOPE-JAK-STAT combines large language models (LLMs), a natural language-to-code engine, and harmonized public CRC datasets from cBioPortal…”
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Introduction to computational causal inference using reproducible Stata, R, and Python code: A tutorial by Smith, Matthew J., Mansournia, Mohammad A., Maringe, Camille, Zivich, Paul N., Cole, Stephen R., Leyrat, Clémence, Belot, Aurélien, Rachet, Bernard, Luque‐Fernandez, Miguel A.

“…The main purpose of many medical studies is to estimate the effects of a treatment or exposure on an outcome. However, it is not always possible to randomize…”
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Percolation theory using Python by Malthe-Sørenssen, Anders

“… Readers will learn how to generate, analyze, and comprehend data and models, with detailed theoretical discussions complemented by accessible computer codes…”
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Statistical analysis of feature-based molecular networking results from non-targeted metabolomics data by Pakkir Shah, Abzer K., Walter, Axel, Ottosson, Filip, Russo, Francesco, Navarro-Diaz, Marcelo, Boldt, Judith, Kalinski, Jarmo-Charles J., Kontou, Eftychia Eva, Elofson, James, Polyzois, Alexandros, González-Marín, Carolina, Farrell, Shane, Aggerbeck, Marie R., Pruksatrakul, Thapanee, Chan, Nathan, Wang, Yunshu, Pöchhacker, Magdalena, Brungs, Corinna, Cámara, Beatriz, Caraballo-Rodríguez, Andrés Mauricio, Cumsille, Andres, de Oliveira, Fernanda, Dührkop, Kai, El Abiead, Yasin, Geibel, Christian, Graves, Lana G., Hansen, Martin, Heuckeroth, Steffen, Knoblauch, Simon, Kostenko, Anastasiia, Kuijpers, Mirte C. M., Mildau, Kevin, Papadopoulos Lambidis, Stilianos, Portal Gomes, Paulo Wender, Schramm, Tilman, Steuer-Lodd, Karoline, Stincone, Paolo, Tayyab, Sibgha, Vitale, Giovanni Andrea, Wagner, Berenike C., Xing, Shipei, Yazzie, Marquis T., Zuffa, Simone, de Kruijff, Martinus, Beemelmanns, Christine, Link, Hannes, Mayer, Christoph, van der Hooft, Justin J. J., Damiani, Tito, Pluskal, Tomáš, Dorrestein, Pieter, Stanstrup, Jan, Schmid, Robin, Wang, Mingxun, Aron, Allegra, Ernst, Madeleine, Petras, Daniel

“… We provide explanations and code in two scripting languages (R and Python) as well…”
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Statistics Using Python by Campesato, Oswald

“…This book is designed to offer a fast-paced yet thorough introduction to essential statistical concepts using Python code samples, and aims to assist data scientists in their daily endeavors…”
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From code to reliability: Python-powered Paraconsistent Logic for alarm detection in the power gris/ Do codigo a confiabilidade: Logica Paraconsistente impulsionada por Python para a deteccao de alarmes na rede de energia by de Oliveira, Joseffe Barroso, Gino, Joao Vitor Santa Rosa, de Lima, Carlos Jose, Filho, Joao Inacio da Silva

“… This application enables the comparison of triggered alarms with the resultant logical states obtained during the analysis…”
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Generation of Scale-Free Assortative Networks via Newman Rewiring for Simulation of Diffusion Phenomena by Di Lucchio, Laura, Modanese, Giovanni

“…By collecting and expanding several numerical recipes developed in previous work, we implement an object-oriented Python code, based on the networkX library, for the realization of the configuration…”
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False Discovery Rate Smoothing by Tansey, Wesley, Koyejo, Oluwasanmi, Poldrack, Russell A., Scott, James G.

“…We present false discovery rate (FDR) smoothing, an empirical-Bayes method for exploiting spatial structure in large multiple-testing problems. FDR smoothing…”
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Trimmed Constrained Mixed Effects Models: Formulations and Algorithms by Zheng, Peng, Barber, Ryan, Sorensen, Reed J. D., Murray, Christopher J. L., Aravkin, Aleksandr Y.

“…Mixed effects (ME) models inform a vast array of problems in the physical and social sciences, and are pervasive in meta-analysis…”
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Estimating Local Prevalence of Obesity Via Survey Under Cost Constraints: Stratifying ZCTAs in Virginia's Thomas Jefferson Health District by Lobo, Benjamin J., Bonds, Denise E., Kafadar, Karen

“… (here, ZIP Code Tabulation Areas, or ZCTAs) prior to conducting the survey for those situations where cost considerations make it infeasible to sample each geographic unit (here, ZCTA) in the region (here, TJHD…”
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Prediction of Positive Patient Health Questionnaire-2 Screening Using Area Deprivation Index in Primary Care by Duarte, Martha, Salamanca, Mayra, Gonzalez, Juan M, Roman Laporte, Roberto, Gattamorta, Karina, Lopez Martinez, Fernando Enrique, Clochesy, John, Rincon Acuna, Juan Carlos

“…Depression is recognized as a significant public health issue in the United States. The National Survey on Drug Use and Health reports that 21.0 million adults…”
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A Review of Adversarial Attack and Defense for Classification Methods by Li, Yao, Cheng, Minhao, Hsieh, Cho-Jui, Lee, Thomas C. M.

“…Despite the efficiency and scalability of machine learning systems, recent studies have demonstrated that many classification methods, especially Deep Neural…”
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Black Box Variational Bayesian Model Averaging by Kejzlar, Vojtech, Bhattacharya, Shrijita, Son, Mookyong, Maiti, Tapabrata

“…For many decades now, Bayesian Model Averaging (BMA) has been a popular framework to systematically account for model uncertainty that arises in situations…”
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Manifold lifting: scaling Markov chain Monte Carlo to the vanishing noise regime by Au, Khai Xiang, Graham, Matthew M, Thiery, Alexandre H

“…Standard Markov chain Monte Carlo methods struggle to explore distributions that concentrate in the neighbourhood of low-dimensional submanifolds. This…”
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Much Ado About Survey Tables: A Comparison of Chi-Square Tests and Software to Analyze Categorical Survey Data by Hu, Li-Yen R., He, Yulei, Irimata, Katherine E., Beresovsky, Vladislav

“… This article aims to fill such a gap. Many modern statistical software packages for survey analysis are capable of computing either the Wald Chi-square test or the Rao…”
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Domain-specific decision modelling and statistical analysis for combat system effectiveness simulation by Li, Xiaobo, Lei, Yonglin, Vangheluwe, Hans, Wang, Weiping, Li, Qun

“… decision models to Python code which is supported by a Python script framework to implement decision models and we present a Bayesian network-based statistical analysis method on simulation output data…”
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Robust distributed precision matrix estimation for high-dimensional data by Ye, Yangqing, Yu, Yang, Ma, Xiaoyan, Liang, Wanfeng

“… Simulation studies and real data analysis demonstrate the superiority of the proposed method. The complete Python code supporting this study can be downloaded from https://github.com/littletesla/RDPM …”
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Graph analysis and visualization: discovering business opportunity in linked data by Brath, Richard, Jonker, David

“… The companion website offers data sets, full code examples in Python, and links to all the tools covered in the book…”
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Fitting deep neural networks into the statistical regression modelling setting by Ha, Il Do, Burke, Kevin

“… The Appendix provides Python codes for a TensorFlow-Keras implementation so that a GLM-based DNN becomes directly accessible to interested readers, including the codes of Cox-based DNN…”
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Spatial Analysis Using Big Data by Hajime Seya, Yoshiki Yamagata

“…Spatial Analysis Using Big Data: Methods and Urban Applications helps readers understand the most powerful, state-of-the-art spatial econometric methods, focusing particularly on urban research problems…”
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