Neural spiking for causal inference and learning. by Benjamin James Lansdell, Konrad Paul Kording

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Research Progress of Causal Inference in Bias Elimination by Chen Limanxi

“…Experimental results indicate that although causal inference methods have eliminated bias to some extent, further research and optimization are still needed. …”
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Causal inference and machine learning in endocrine epidemiology by Kosuke Inoue

Subjects: “…causal inference…”
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Practically effective adjustment variable selection in causal inference by Atsushi Noda, Takashi Isozaki

Subjects: “…causal inference…”
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Modelling sensory attenuation as Bayesian causal inference across two datasets. by Anna-Lena Eckert, Elena Fuehrer, Christina Schmitter, Benjamin Straube, Katja Fiehler, Dominik Endres

“…We propose a computational model of sensory attenuation (SA) based on Bayesian Causal Inference, where SA occurs when an internal cause for sensory information is inferred.…”
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The Impact of Positive Fluid Balance on Sepsis Subtypes: A Causal Inference Study by Sharad Patel, Adam Green, Yanika Wolfe, Gregory Felock, Samantha Epstein, Nitin Puri

“…Sepsis, the leading cause of death in hospitalized patients globally, was investigated in this study, examining the varying effects of positive fluid balance on sepsis subtypes through causal inference. Methods. In this study, data from the eICU database were utilized, extracting 35 features from sepsis patients. …”
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Impact of empiric antibiotics on risk of Clostridioides difficile—a causal inference observational analysis by Matthew A. Pappas, Shoshana J. Herzig, Andrew D. Auerbach, Abhishek Deshpande, Eunice Blanchard, Michael B. Rothberg

“…Conclusions: Among common empiric antibiotics, parenteral vancomycin and cefepime appeared to increase risk of hospital-onset CDI. Causal inference observational study designs can be used to estimate patient-level harms of interventions such as empiric antimicrobials. …”
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Causal Inference for Hypertension Prediction With Wearable E lectrocardiogram and P hotoplethysmogram Signals: Feasibility Study by Ke Gon g, Yifan Chen, Xinyue Song, Zhizhong Fu, Xiaorong Ding

“…Conclusions The results indicated that the causal inference –based approach can potentially clarify the mechanism of hypertension detection with noninvasive signals and effectively detect hypertension. …”
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The Impact of Farmland Transfer on Urban–Rural Integration: Causal Inference Based on Double Machine Learning by Yuchen Lu, Jiakun Zhuang, Jun Chen, Chenlu Yang, Mei Kong

“…The analysis of the impact of the 2010 liberalisation of the land transfer policy employs a dual machine learning model, utilising provincial-level data from China spanning 2005 to 2022, to address the limitations of traditional causal inference models while ensuring estimation accuracy. …”
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Comparative analysis of correlation and causality inference in water quality problems with emphasis on TDS Karkheh River in Iran by Reza Shakeri, Hossein Amini, Farshid Fakheri, Man Yue Lam, Banafsheh Zahraie

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Similar Survival Between Non-Western Immigrant Patients and Danish-Born Patients with Lymphoma: A Danish Population-Based Study by Simonsen MR, Maksten EF, Jakobsen LH, Severinsen MT, Dann EJ, Frederiksen H, Niemann CU, Jørgensen JM, Clausen MR, Starklint J, Johnsen SP, El-Galaly TC, Baech J

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Diabetes Prediction Through Linkage of Causal Discovery and Inference Model with Machine Learning Models by Mi Jin Noh, Yang Sok Kim

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Causally inferred evidence of the impact of green and blue spaces (GBS) on maternal and neonatal health: a systematic review and meta-analysis by Rukun K S Khalaf, Selin Akaraci, Faye D Baldwin, Rebecca S Geary, Ruwanthi Kolamunnage-Dona, Ruth F Hunter, Sarah E Rodgers

“…This does not allow for causal inference. Thus, our systematic review aimed to analyse the evidence of the impact of GBS on maternal, prenatal, and/or neonatal health. …”
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Analyzing the relationship between gene expression and phenotype in space-flown mice using a causal inference machine learning ensemble by James A. Casaletto, Ryan T. Scott, Makenna Myrick, Graham Mackintosh, Hamed Chok, Amanda Saravia-Butler, Adrienne Hoarfrost, Jonathan M. Galazka, Lauren M. Sanders, Sylvain V. Costes

“…In this work, we use a machine learning ensemble of causal inference methods called the Causal Research and Inference Search Platform (CRISP) which was developed to predict causal features of a binary response variable from high-dimensional input. …”
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A novel framework for assessing causal effect of microbiome on health: long-term antibiotic usage as an instrument by Nele Taba, Krista Fischer, Estonian Biobank Research Team, Elin Org, Oliver Aasmets

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Defining the Need for Causal Inference to Understand the Impact of Social Determinants of Health: A Primer on Behalf of the Consortium for the Holistic Assessment of Risk in Transplantation (CHART) by Nrupen A. Bhavsar, PhD, Rachel E. Patzer, PhD, David J. Taber, PharmD, Katie Ross-Driscoll, PhD, Rhiannon Deierhoi Reed, PhD, Juan C. Caicedo-Ramirez, MD, Elisa J. Gordon, PhD, MPH, Roland A. Matsouaka, PhD, Ursula Rogers, BS, Wendy Webster, MBA, Andrew Adams, MD, PhD, Allan D. Kirk, MD, Lisa M. McElroy, MD

“…Designing studies to quantify the causal impact of these factors on transplant access and outcomes requires an understanding of the fundamental concepts of causal inference. Methods:. We present an overview of fundamental concepts in causal inference, including the potential outcomes framework and direct acyclic graphs. …”
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Causal relationship between immune cells and risk of heart failure: evidence from a Mendelian randomization study by Wenjing Cao, Zefu Yang, Liumei Mo, Zhenhao Liu, Jiawei Wang, Zhenhong Zhang, Kui Wang, Wei Pan

Subjects: “…causal inference…”
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Assessing the Causal Relationship Between Various Immune Cells and Attention Deficit Hyperactivity Disorder: Mendelian Randomization Study by Qian Ge, Zhongyan Li, Weijing Meng, Chen Cai, Mengdi Qiu, Yafei Liu, Haibo Zhu

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Decision making, symmetry and structure: Justifying causal interventions by Johnston David O., Ong Cheng Soon, Williamson Robert C.

Subjects: “…causal inference…”
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The economic impact of next-generation stadiums: evidence from the Juventus Stadium using synthetic control methodology by Valerio Antolini

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