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| http://dx.doi.org/10.1111/biom.12784 | DOI Listing |
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A novel generative multi-task representation learning approach for predicting postoperative complications in cardiac surgery patients.
J Am Med Inform Assoc
December 2024
AI for Health Institute, Washington University in St Louis, St Louis, MO 63130, United States.
Objective: Early detection of surgical complications allows for timely therapy and proactive risk mitigation. Machine learning (ML) can be leveraged to identify and predict patient risks for postoperative complications. We developed and validated the effectiveness of predicting postoperative complications using a novel surgical Variational Autoencoder (surgVAE) that uncovers intrinsic patterns via cross-task and cross-cohort presentation learning.
View Article and Find Full Text PDFMIIVefa: An R Package for a New Type of Exploratory Factor Anaylysis Using Model-Implied Instrumental Variables.
Multivariate Behav Res
December 2024
Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
We present the R package MIIVefa, designed to implement the MIIV-EFA algorithm. This algorithm explores and identifies the underlying factor structure within a set of variables. The resulting model is not a typical exploratory factor analysis (EFA) model because some loadings are fixed to zero and it allows users to include hypothesized correlated errors such as might occur with longitudinal data.
View Article and Find Full Text PDFEvidence of compensatory neural hyperactivity in a subgroup of breast cancer survivors treated with chemotherapy and its association with brain aging.
Front Aging Neurosci
December 2024
Division of Adult Health, School of Nursing, University of Texas at Austin, Austin, TX, United States.
Introduction: Chemotherapy-related cognitive impairment (CRCI) remains poorly understood in terms of the mechanisms of cognitive decline. Neural hyperactivity has been reported on average in cancer survivors, but it is unclear which patients demonstrate this neurophenotype, limiting precision medicine in this population.
Methods: We evaluated a retrospective sample of 80 breast cancer survivors and 80 non-cancer controls, aged 35-73, for which we had previously identified and validated three data-driven, biological subgroups (biotypes) of CRCI.
Enhancing the reverse transcriptase function in Taq polymerase via AI-driven multiparametric rational design.
Front Bioeng Biotechnol
December 2024
AO Vector-Best, Novosibirsk, Russia.
Introduction: Modification of natural enzymes to introduce new properties and enhance existing ones is a central challenge in bioengineering. This study is focused on the development of Taq polymerase mutants that show enhanced reverse transcriptase (RTase) activity while retaining other desirable properties such as fidelity, 5'- 3' exonuclease activity, effective deoxyuracyl incorporation, and tolerance to locked nucleic acid (LNA)-containing substrates. Our objective was to use AI-driven rational design combined with multiparametric wet-lab analysis to identify and validate Taq polymerase mutants with an optimal combination of these properties.
View Article and Find Full Text PDFCapturing Catchment Area Data Comprehensively: The North Carolina Cancer Health Assets and Needs Assessment (CHANA) Approach.
Prev Oncol Epidemiol
June 2024
Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina.
Background: A key requirement of community outreach and engagement offices within National Cancer Institute-designated cancer centers is to conduct a comprehensive examination of their catchment area's population, cancer burden, and assets. To accomplish this task, we describe the plan for implementing our initiative, the Cancer Health Assets and Needs Assessment (CHANA). CHANA compiles, into a single source, up-to-date data that describes the cancer landscape of North Carolina's 100 counties.
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