Results 81 to 90 of about 132,485,236 (247)

MLFLHMDA: predicting human microbe-disease association based on multi-view latent feature learning

Frontiers in Microbiology
IntroductionA growing body of research indicates that microorganisms play a crucial role in human health. Imbalances in microbial communities are closely linked to human diseases, and identifying potential relationships between microbes and diseases can ...
Ziwei Chen, Liangzhe Zhang, Jingyi Li, Mingyang Fu   +3 more
doaj   +1 more source

Profiling neoadjuvant therapy response in rectal cancer using meta‐analysis of publicly available transcriptomic RNA‐seq datasets

Molecular Oncology, EarlyView.
This study integrates publicly available transcriptomic datasets to identify molecular signatures associated with response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. By analyzing a combination of multiple cohorts with bioinformatics approaches, we reveal biological pathways and immune‐related features that may improve ...
Aleksandra Stanojevic, Rafael Stroggilos, Mladen Marinkovic, Ana Djuric, Suzana Stojanovic‐Rundic, Radmila Jankovic, Sergi Castellvi‐Bel, Remond J.A. Fijneman, Antonia Vlahou, Jerome Zoidakis, Milena Cavic   +10 more
wiley   +1 more source

Machine Learning Prediction of 28-Day Compressive Strength in Recycled Aggregate Concretes with Supplementary Cementitious Materials: Experimental Validation Using Metakaolin and Spent Fluid Catalytic Cracking Catalyst Residue

Modelling
This study develops an interpretable machine learning framework for predicting the 28-day compressive strength of recycled aggregate concrete containing supplementary cementitious materials and validates it experimentally using metakaolin and spent fluid
Jesús E. Altamiranda-Ramos, Luis Castillo-Suárez, Joaquín Abellán-García   +2 more
doaj   +1 more source

Extracellular vesicle lipidomics liquid biopsy reveals systemic and tumor microenvironment metabolic reprogramming in ovarian cancer

Molecular Oncology, EarlyView.
Extracellular vesicle (EV) lipidomic profiling of plasma and ascites from patients with high‐grade serous ovarian cancer and of ovarian cancer cell lines reveals enrichment of triglycerides (TGs), diacylglycerols (DGs), phosphatidylcholine (PCs), sphingomyelins (SMs), reflecting tumor metabolic reprogramming.
Shikha Rani, Dominic Guanzon, Andrew Lai, Katherin Scholz‐Romero, Sarah Reed, Edita Ritmejeryte, Rohan Lourie, Naven Chetty, Kaltin Ferguson, Carlos Salomon   +9 more
wiley   +1 more source

Anti-Diabetic Therapeutic Medicinal Plant Identification Using Deep Fused Discriminant Subspace Ensemble (D2SE).

International Journal of Interactive Multimedia and Artificial Intelligence
About 422 million people worldwide have diabetes, the majority living in low-and middle-income countries, and 1.5 million deaths are directly attributed to diabetes each year.
N. Sasikaladevi, S. Pradeepa, A. Revathi, S. Vimal, Gaurav Dhiman   +4 more
doaj   +1 more source

Time series classification using k-Nearest neighbours, Multilayer Perceptron and Learning Vector Quantization algorithms

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2012
We are presenting results comparison of three artificial intelligence algorithms in a classification of time series derived from musical excerpts in this paper.
Jiří Fejfar, Jiří Šťastný, Miroslav Cepl   +2 more
doaj   +1 more source

Predictive and prognostic biomarkers of Bacillus Calmette‐Guérin therapy failure in bladder cancer patients: A systematic review

Molecular Oncology, EarlyView.
High‐risk bladder cancer is typically treated with Bacillus Calmette‐Guérin (BCG), but 30–40% of patients relapse. No FDA‐ or CE‐approved biomarkers currently predict or prognosticate BCG failure. We systematically reviewed the literature and identified 72 eligible studies, revealing several promising biomarkers associated with BCG treatment response ...
Rui Ribeiro‐Pereira, Ana Teixeira‐Marques, Rui Freitas, João A Carvalho, Sara Monteiro‐Reis, Giorgio I. Russo, Rui Henrique, Carmen Jerónimo   +7 more
wiley   +1 more source

Computing the Nearest Doubly Stochastic Matrix with A Prescribed Entry ∗

, 2006
In this paper a nearest doubly stochastic matrix problem is studied. This problem is to find the closest doubly stochastic matrix with the prescribed (1, 1) entry to a given matrix.
Zheng-jian Bai, Roger C. E. Tan, Delin Chu   +2 more
core  

One Dimensional Median Local Binary Pattern Based Feature Extraction For Classifying Epileptic EEG Signals

Gazi Üniversitesi Fen Bilimleri Dergisi, 2017
Electroencephalogram is an important data source that widely used in detecting epilepsy. In this study, EEG records consisting of five markers A, B, C, D, E that obtained from the database of Epilogy of Bonn University Epileptology Department was used ...
Ömer Türk, Mehmet Siraç Özerdem
doaj  

Hyperparameter-Tuned K-Nearest Neighbor for Herbal Leaf Classification Using Shape, Color, and Texture Feature Fusion in Smart Agriculture

Journal of Information Systems and Informatics
This study develops a lightweight K-Nearest Neighbor (K-NN) classifier to identify five Indonesian herbal leaf species—betel, bay, guava, soursop, and moringa—for potential smart-agriculture applications.
Avip Kurniawan, Agustinus Eko Setiawan, Vevi Maritha, Muhammad Abrar Argianata   +3 more
doaj   +1 more source