Article
Behavioral Sciences
Anna Elisabeth Furtjes
Summary: The research fields of Complex Trait (or Statistical) Genetics and Neuroimaging face similar challenges, and lessons learned from genetics research, such as abandoning simplistic studies, increasing sample sizes, and utilizing large-scale collaboration and meta-analysis, can be directly applicable to neuroimaging research to accelerate its evolution.
Article
Engineering, Aerospace
Peng He, Ruishan Sun
Summary: Efficient management of aviation safety requires accurate analysis of incident trends. This study proposes a causal-ARIMA model grounded in causal inference theory and employs four different modeling strategies to fit the trend of incidents in China's civil aviation sector from 1994 to 2020. The findings reveal that ensemble techniques incorporating the causal-ARIMA model outperform classical trend analysis methods in terms of model fit.
Article
Physics, Fluids & Plasmas
Jean-Gabriel Young, Alec Kirkley, M. E. J. Newman
Summary: This article describes a Bayesian analysis framework for handling data with multiple possible structures in network reconstruction. By defining a finite mixture model and Gibbs sampling procedure, the measured networks are clustered into groups with similar structure.
Article
Urology & Nephrology
Rui Fu, S. Joseph Kim
Summary: Inferring causality from observational studies is challenging due to biases, but randomized controlled trials are the gold standard in clinical research. However, many clinically relevant exposure-outcome relationships cannot be randomized, leading to the emergence of analytical approaches like instrumental variable analysis. This review introduces instrumental variable analysis, its assumptions, and recent applications in nephrology outcomes research.
KIDNEY INTERNATIONAL
(2021)
Article
Mechanics
Hanwen Huang, Qinglong Yang
Summary: The article explores the performance of margin-based classifiers under two component mixture models in situations of large data dimension and sample size, revealing a close match between the asymptotic results described by nonlinear equations and Monte Carlo simulation on finite data samples. The study sheds new light on selecting the best classifier among various classification methods and choosing optimal tuning parameters for a given method.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2021)
Article
Mechanics
Annabel L. Davies, Tobias Galla
Summary: This article introduces the application of network meta-analysis in medical statistics and discusses the potential role of statistical physics in this field. It aims to present the 'NMA problem' and existing approaches to statistical physicists in an accessible language, and attract physicists to engage in this interesting and worthwhile research area.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2022)
Article
Physics, Multidisciplinary
Anmol Dwivedi, Sihui Wang, Ali Tajer
Summary: This paper investigates the optimal design of linear dimensionality reduction to maximize the preservation of divergence between models. By analyzing Gaussian models, the study finds the optimal design for linear data transformation and explores different divergence measures. The research reveals that, under zero-mean Gaussian models, projections are not necessarily along the largest modes of the covariance matrix, and the optimal design remains the same across different divergence measures.
Review
Psychology, Mathematical
Johnny van Doorn, Don van den Bergh, Udo Bohm, Fabian Dablander, Koen Derks, Tim Draws, Alexander Etz, Nathan J. Evans, Quentin F. Gronau, Julia M. Haaf, Max Hinne, Simon Kucharsky, Alexander Ly, Maarten Marsman, Dora Matzke, Akash R. Komarlu Narendra Gupta, Alexandra Sarafoglou, Angelika Stefan, Jan G. Voelkel, Eric-Jan Wagenmakers
Summary: Although there is a lack of practical guidelines on how to apply Bayesian procedures and interpret results in empirical research, this study offers specific guidance for four stages of Bayesian statistical reasoning in a research setting: planning the analysis, executing the analysis, interpreting the results, and reporting the results. Each stage's guidelines are illustrated with a running example, primarily focusing on analyses performed with the open-source statistical software JASP, but with applicability to Bayesian inference in general.
PSYCHONOMIC BULLETIN & REVIEW
(2021)
Article
Neurosciences
Melodie Derome, Petya Kozuharova, Andreea O. Diaconescu, Sophie Deneve, Renaud Jardri, Paul Allen
Summary: The study investigates the presence of central inference mechanism in individuals with high schizotypy traits and its neurobiological basis associated with sensory amplification. The findings reveal changes in central inference parameters, altered cortical excitatory neurotransmission, and altered resting state functional connectivity related to sensory amplification in individuals with high schizotypy traits.
Article
Behavioral Sciences
Ladan Shams, Ulrik Beierholm
Summary: The theory of Bayesian causal inference is a powerful and versatile theory that can explain human behavior and brain function, making it highly significant in neuroscience research.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
(2022)
Article
Food Science & Technology
Maryia Bakhtsiyarava, Tim G. Williams, Andrew Verdin, Seth D. Guikema
Summary: This study uses nonparametric regression methods to analyze the relationship between food insecurity and household survey data, revealing complex nonlinear and threshold relationships between food security measures, livestock ownership, and climatic conditions. The findings suggest that policy decisions should take into account nonlinearity, and that random forest and other nonparametric methods may be particularly useful in uncovering nuances in these relationships during suboptimal climatic conditions.
Article
Multidisciplinary Sciences
David J. Halpern, Shannon Tubridy, Lila Davachi, Todd M. Gureckis
Summary: Over 40 years of research have shown associations between neuroimaging signals during memory encoding tasks and future memory performance. However, the interpretation of these subsequent memory effects (SMEs) is still unclear. Previous studies did not control for potential confounders of these effects. In this study, a large fMRI dataset was collected and adjusted for known confounding variables. The results suggest that existing neuroimaging measures may not have the precision and specificity to reliably predict subsequent memory.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2023)
Article
Engineering, Multidisciplinary
M. Nagy, M. E. Bakr, Adel Fahad Alrasheedi
Summary: In this article, the maximum likelihood estimation and Bayesian inference are discussed for a generalized Type-II progressive hybrid censoring sample from the Burr Type-XII distribution. Point and interval estimates, as well as reliability and hazard function estimations of unknown parameters, are developed. Different loss functions and prior distributions are employed for symmetric and asymmetric inferences. Additionally, a Bayesian one-sample prediction method is proposed for unobserved failures under the generalized Type-II progressive hybrid censoring sample. Simulation studies and real data applications are conducted to validate the theoretical results.
MATHEMATICAL PROBLEMS IN ENGINEERING
(2022)
Article
Mathematics
Ahsan Bin Tufail, Yong-Kui Ma, Mohammed K. A. Kaabar, Ateeq Ur Rehman, Rahim Khan, Omar Cheikhrouhou
Summary: Alzheimer's disease (AD) is a major health concern for the elderly population globally, characterized by amyloid plaques, neurofibrillary tangles, and neuronal loss. Neuroimaging techniques like PET and MRI are commonly used in clinical settings to monitor brain changes in AD. Deep learning techniques and image filtering methods play crucial roles in improving the effectiveness of neuroimaging data.
Article
Meteorology & Atmospheric Sciences
Farshad Jalili Pirani, Mohammad Reza Najafi, Paul Joe, Julian Brimelow, Gordon Mcbean, Meghdad Rahimian, Ronald Stewart, Paul Kovacs
Summary: This study analyzed a ten-year set of hailstorm events in Alberta, Canada, and evaluated the potential effects of cloud seeding on hailstorms. The results suggest that cloud seeding may reduce the hail damage potential of storms, especially those with high VILmax values.
ATMOSPHERIC RESEARCH
(2023)
Article
Medicine, General & Internal
Michael J. Mack, Michael A. Acker, Annetine C. Gelijns, Jessica R. Overbey, Michael K. Parides, Jeffrey N. Browndyke, Mark A. Groh, Alan J. Moskowitz, Neal O. Jeffries, Gorav Ailawadi, Vinod H. Thourani, Ellen G. Moquete, Alexander Iribarne, Pierre Voisine, Louis P. Perrault, Michael E. Bowdish, Michel Bilello, Christos Davatzikos, Ralph F. Mangusan, Rachelle A. Winkle, Peter K. Smith, Robert E. Michler, Marissa A. Miller, Karen L. O'Sullivan, Wendy C. Taddei-Peters, Eric A. Rose, Richard D. Weisel, Karen L. Furie, Emilia Bagiella, Claudia Scala Moy, Patrick T. O'Gara, Steven R. Messe
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION
(2017)
Article
Neurosciences
Sahba Seddighi, Vijay R. Varma, Yang An, Sudhir Varma, Lori L. Beason-Held, Toshiko Tanaka, Melissa H. Kitner-Triolo, Michael A. Kraut, Christos Davatzikos, Madhav Thambisetty
JOURNAL OF ALZHEIMERS DISEASE
(2018)
Article
Biochemical Research Methods
N. Honnorat, T. D. Satterthwaite, R. E. Gur, R. C. Gur, C. Davatzikos
JOURNAL OF NEUROSCIENCE METHODS
(2017)
Article
Clinical Neurology
Jared M. Pisapia, Martin Rozycki, Flamed Akbari, Spyridon Bakas, Jayesh P. Thawani, Julie S. Moldenhauer, Phillip B. Storm, Deborah M. Zarnow, Christos Davatzikos, Gregory G. Heuer
JOURNAL OF NEUROSURGERY-PEDIATRICS
(2017)
Article
Radiology, Nuclear Medicine & Medical Imaging
Cuong Viet Dinh, Peter Steenbergen, Ghazaleh Ghobadi, Henk van der Poel, Stijn W. T. P. J. Heijmink, Jeroen de Jong, Sofi E. Isebaert, Karin Haustermans, Evelyne Lerut, Raymond Oyen, Yangming Ou, Davatzikos Christos, Uulke A. van der Heide
Article
Clinical Neurology
Thomas F. Tropea, Sharon X. Xie, Jacqueline Rick, Lana M. Chahine, Nabila Dahodwala, Jimit Doshi, Christos Davatzikos, Leslie M. Shaw, Vivianna Van Deerlin, John Q. Trojanowski, Daniel Weintraub, Alice S. Chen-Plotkin
MOVEMENT DISORDERS
(2018)
Article
Neurosciences
Erdem Varol, Aristeidis Sotiras, Christos Davatzikos
Article
Neurosciences
Rastko Ciric, Daniel H. Wolf, Jonathan D. Power, David R. Roalf, Graham L. Baum, Kosha Ruparel, Russell T. Shinohara, Mark A. Elliott, Simon B. Eickhoff, Christos Davatzikos, Ruben C. Gur, Raquel E. Gur, Danielle S. Bassett, Theodore D. Satterthwaite
Review
Neurosciences
Saima Rathore, Mohamad Habes, Muhammad Aksam Iftikhar, Amanda Shacklett, Christos Davatzikos
Article
Neurosciences
Guray Erus, Jimit Doshi, Yang An, Dimitris Verganelakis, Susan M. Resnick, Christos Davatzikos
Article
Neurosciences
Adon F. G. Rosen, David R. Roalf, Kosha Ruparel, Jason Blake, Kevin Seelaus, Lakshmi P. Villa, Rastko Ciric, Philip A. Cook, Christos Davatzikos, Mark A. Elliott, Angel Garcia de La Garza, Efstathios D. Gennatas, Megan Quarmley, J. Eric Schmitt, Russell T. Shinohara, M. Dylan Tisdall, R. Cameron Craddock, Raquel E. Gur, Ruben C. Gur, Theodore D. Satterthwaite
Proceedings Paper
Engineering, Biomedical
Linmin Pei, Syed M. S. Reza, Wei Li, Christos Davatzikos, Khan M. Iftekharuddin
MEDICAL IMAGING 2017: COMPUTER-AIDED DIAGNOSIS
(2017)
Article
Clinical Neurology
R. T. Shinohara, J. Oh, G. Nair, P. A. Calabresi, C. Davatzikos, J. Doshi, R. G. Henry, G. Kim, K. A. Linn, N. Papinutto, D. Pelletier, D. L. Pham, D. S. Reich, W. Rooney, S. Roy, W. Stern, S. Tummala, F. Yousuf, A. Zhu, N. L. Sicotte, R. Bakshi
AMERICAN JOURNAL OF NEURORADIOLOGY
(2017)
Article
Psychiatry
Anup Sharma, Daniel H. Wolf, Rastko Ciric, Joseph W. Kable, Tyler M. Moore, Simon N. Vandekar, Natalie Katchmar, Aylin Daldal, Kosha Ruparel, Christos Davatzikos, Mark A. Elliott, Monica E. Calkins, Russell T. Shinohara, Danielle S. Bassett, Theodore D. Satterthwaite
AMERICAN JOURNAL OF PSYCHIATRY
(2017)
Proceedings Paper
Computer Science, Theory & Methods
Amir Gholami, Andreas Mang, Klaudius Scheufele, Christos Davatzikos, Miriam Mehl, George Biros
SC'17: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE FOR HIGH PERFORMANCE COMPUTING, NETWORKING, STORAGE AND ANALYSIS
(2017)
Article
Neurosciences
Jose Sanchez-Bornot, Roberto C. Sotero, J. A. Scott Kelso, Ozguer Simsek, Damien Coyle
Summary: This study proposes a multi-penalized state-space model for analyzing unobserved dynamics, using a data-driven regularization method. Novel algorithms are developed to solve the model, and a cross-validation method is introduced to evaluate regularization parameters. The effectiveness of this method is validated through simulations and real data analysis, enabling a more accurate exploration of cognitive brain functions.