Results 51 to 60 of about 155,351 (242)

Causal Structure Learning [PDF]

Annual Review of Statistics and Its Application, 2018
Graphical models can represent a multivariate distribution in a convenient and accessible form as a graph. Causal models can be viewed as a special class of graphical models that represent not only the distribution of the observed system but also the distributions under external interventions.
Heinze-Deml, Christina, Maathuis, Marloes H., Meinshausen, Nicolai   +2 more
openaire   +2 more sources

Tumor mutational burden as a determinant of metastatic dissemination patterns

Molecular Oncology, EarlyView.
This study performed a comprehensive analysis of genomic data to elucidate whether metastasis in certain organs share genetic characteristics regardless of cancer type. No robust mutational patterns were identified across different metastatic locations and cancer types.
Eduardo Candeal, Andrea Moreno‐Manuel, Miguel Salvadó‐Pertierra, Cristina Santos‐Vivas, Rebeca Sanz‐Pamplona   +4 more
wiley   +1 more source

Addressing Hybrid Confounder Issue for Causal Session-Based Recommendation

IEEE Access
In the field of session-based recommendation, users’ interaction behaviors are affected by both popularity and surrounding environmental factors, such as item popularity, season, or salary, and so on.
Quan Li, Xinhua Xu, Jinjun Liu, Guangmin Li   +3 more
doaj   +1 more source

Instrumental Causal Learning

, 2023
Causal learning has traditionally been regarded as a process of forming epistemically accurate causal beliefs that represent the world. Yet, considering that a primary function of causal learning is to further people’s practical goals by increasing their control over their surroundings, perhaps people also evaluate the instrumental value of causal ...
Dennis W. H. Teo, Desmond C. Ong
openaire   +1 more source

RaMBat: Accurate identification of medulloblastoma subtypes from diverse data sources with severe batch effects

Molecular Oncology, EarlyView.
To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

Illusions of causality: How they bias our everyday thinking and how they could be reduced

Frontiers in Psychology, 2015
Illusions of causality occur when people develop the belief that there is a causal connection between two events that are actually unrelated. Such illusions have been proposed to underlie pseudoscience and superstitious thinking, sometimes leading to ...
Helena eMatute, Fernando eBlanco, Ion eYarritu, Marcos eDiaz-Lago, Miguel A. Vadillo, Itxaso ebarberia   +5 more
doaj   +1 more source

Genetic attenuation of ALDH1A1 increases metastatic potential and aggressiveness in colorectal cancer

Molecular Oncology, EarlyView.
Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova, Zuzana Kozovska, Ondrej Pos, Kristina Pavlov, Sachin Gulati, Peter Makovicky, Kristina Jakic, Monika Burikova, Eva Sedlackova, Barbora Svitkova, Silvia Tyciakova, Vojtech Bystry, Nicolas Blavet, Boris Tichy, Matej Hrnciar, Jaroslav Budis, Miroslav Tomas, Peter Dubovan, Georgina Kolnikova, Veronika Repaska, Nikoleta Mojzesova, Eva Zomborska, Daniel Pindak, Michal Mego, Tomas Szemes, Miroslava Matuskova   +25 more
wiley   +1 more source

Overview of molecular signatures of senescence and associated resources: pros and cons

FEBS Open Bio, EarlyView.
Cells can enter a stress response state termed cellular senescence that is involved in various diseases and aging. Detecting these cells is challenging due to the lack of universal biomarkers. This review presents the current state of senescence identification, from biomarkers to molecular signatures, compares tools and approaches, and highlights ...
Orestis A. Ntintas, Sylvia Vagena, Pavlos Pantelis, Giorgos Theocharous, Russel Petty, Konstantinos Evangelou, Vassilis G. Gorgoulis   +6 more
wiley   +1 more source

Deep Learning–Assisted Differentiation of Four Peripheral Neuropathies Using Corneal Confocal Microscopy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah, Ioannis N. Petropoulos, Mark Stettner, Maryam Ferdousi, Uazman Alam, Nathan Efron, Ahmed Serag, Rayaz A. Malik   +7 more
wiley   +1 more source

CausMatch: Causal Matching Learning With Counterfactual Preference Framework for Cross-Modal Retrieval

IEEE Access
Cross-modal retrieval exhibits significant promise within the realm of multimedia analysis. Numerous sophisticated techniques have gained widespread adoption for harnessing attention mechanisms to facilitate cross-modal correspondence in matching tasks ...
Chen Chen, Dan Wang
doaj   +1 more source