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| http://dx.doi.org/10.1523/JNEUROSCI.4917-10.2010 | DOI Listing |
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Risk prediction of integrated traditional Chinese and western medicine for diabetes retinopathy based on optimized gradient boosting classifier model.
Medicine (Baltimore)
December 2024
School of Informatics, Hunan University of Chinese Medicine, Changsha, China.
In order to take full advantage of traditional Chinese medicine (TCM) and western medicine, combined with machine learning technology, to study the risk factors and better risk prediction model of diabetic retinopathy (DR), and provide basis for the screening and treatment of it. Through a retrospective study of DR cases in the real world, the electronic medical records of patients who met screening criteria were collected. Moreover, Recursive Feature Elimination with Cross-Validation (RFECV) was used for feature selection.
View Article and Find Full Text PDFForward and backward modeling of cultural evolutionary processes.
Proc Natl Acad Sci U S A
November 2024
Graduate School of Science, University of Tokyo, Hongo, Tokyo 113-0033, Japan.
Modern cultural evolution theory adopts a variety of concepts and methods developed in mathematical biology, in particular population genetics theory. In addition to forward-looking approaches such as two-locus models, backward-looking approaches such as coalescent theory, which describe ancestral states of the current population, have played an important role in population genetics. Here, we show how forward and backward approaches can be applied to two examples in cultural evolution.
View Article and Find Full Text PDFDeciphering the role of lipid metabolism-related genes in Alzheimer's disease: a machine learning approach integrating Traditional Chinese Medicine.
Front Endocrinol (Lausanne)
November 2024
Department of Geriatrics, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Article Synopsis
- Alzheimer’s disease (AD) is a neurodegenerative condition marked by amyloid plaques and tau tangles in the brain, with apolipoprotein E (ApoE) playing a crucial role in its development due to its involvement in lipid metabolism.
- This research aims to identify early-stage AD biomarkers related to immune cell infiltration by leveraging advanced machine learning techniques on gene expression data from the Gene Expression Omnibus (GEO).
- To isolate significant lipid metabolism-related genes (LMDEGs), the study employs differential expression analysis, with a focus on machine learning algorithms to pinpoint a potential key biomarker and its correlation with immune response.
Metabolic biomarkers of neonatal sepsis: identification using metabolomics combined with machine learning.
Front Cell Dev Biol
October 2024
Department of Neonatology, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Background: Sepsis is a common disease associated with neonatal and infant mortality, and for diagnosis, blood culture is currently the gold standard method, but it has a low positivity rate and requires more than 2 days to develop. Meanwhile, unfortunately, the specific biomarkers for the early and timely diagnosis of sepsis in infants and for the determination of the severity of this disease are lacking in clinical practice.
Methods: Samples from 18 sepsis infants with comorbidities, 25 sepsis infants without comorbidities, and 25 infants with noninfectious diseases were evaluated using a serum metabolomics approach based on liquid chromatography‒mass spectrometry (LC‒MS) technology.
Gathering around a satellite image: Visual media cycles of the nuclear nonproliferation complex.
Soc Stud Sci
October 2024
Georgetown University, Washington, DC, USA.
How have Western nongovernmental experts used remote sensing to make public knowledge about Iran's nuclear program? This article recounts several episodes in which experts and journalists congregated around satellite images to uncover hidden nuclear objects in Iran. Drawing from the theoretical tradition of co-production, I describe this recurrent collective experience as an that can both coordinate and transform diverse communities of knowledge. I outline common temporal and thematic structures that define these episodes, and illuminate the role of commercial satellite imagery as material anchor that threads distributed imaginings together such that broadly-shared experience and sensibility can emerge.
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