[This corrects the article DOI: 10.1007/s00477-020-01827-8.].
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7383123 | PMC |
| http://dx.doi.org/10.1007/s00477-020-01843-8 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Bimodal In Situ Analyzer for Circular RNA in Extracellular Vesicles Combined with Machine Learning for Accurate Gastric Cancer Detection.
Adv Sci (Weinh)
January 2025
Department of Laboratory Medicine, Guangdong Provincial Key Laboratory of Precision Medical Diagnostics， Guangdong Engineering and Technology Research Center for Rapid Diagnostic Biosensors， Guangdong Provincial Key Laboratory of Single Cell Technology and Application, School of Laboratory Medicine and Biotechnology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, 510515, P. R. China.
Circular RNAs in extracellular vesicles (EV-circRNAs) are gaining recognition as potential biomarkers for the diagnosis of gastric cancer (GC). Most current research is focused on identifying new biomarkers and their functional significance in disease regulation. However, the practical application of EV-circRNAs in the early diagnosis of GC is yet to be thoroughly explored due to the low accuracy of EV-circRNAs analysis.
View Article and Find Full Text PDFRationalizing Predictions of Isoform-Selective Phosphoinositide 3-Kinase Inhibitors Using MolAnchor Analysis.
J Chem Inf Model
January 2025
Department of Life Science Informatics and Data Science, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Friedrich-Hirzebruch-Allee 5/6, Bonn D-53115, Germany.
Explaining the predictions of machine learning models is of critical importance for integrating predictive modeling in drug discovery projects. We have generated a test system for predicting isoform selectivity of phosphoinositide 3-kinase (PI3K) inhibitors and systematically analyzed correct predictions of selective inhibitors using a new methodology termed MolAnchor, which is based on the "anchors" concept from explainable artificial intelligence. The approach is designed to generate chemically intuitive explanations of compound predictions.
View Article and Find Full Text PDFNeuropsychiatric symptoms and neuroimaging-based brain age in mild cognitive impairment and early dementia: A multicenter study.
Psychiatry Clin Neurosci
January 2025
Department of Neuropsychiatry, Kochi Medical School, Kochi University, Kochi, Japan.
Aim: Despite the clinical importance and significant social burden of neuropsychiatric symptoms (NPS) in dementia, the underlying neurobiological mechanism remains poorly understood. Recently, neuroimaging-derived brain-age estimation by machine-learning analysis has shown promise as an individual-level biomarker. We investigated the relationship between NPS and brain-age in amnestic mild cognitive impairment (MCI) and early dementia.
View Article and Find Full Text PDFPublisher Correction: A generic self-learning emotional framework for machines.
Sci Rep
January 2025
Research Centre for Information and Communications Technologies (CITIC-UGR) - Department of Computer Engineering, Automation, and Robotics (ICAR), University of Granada, 18071, Granada, Spain.
A systematic review of machine learning applications in predicting opioid associated adverse events.
NPJ Digit Med
January 2025
Centre for Epidemiology Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester, United Kingdom.
Machine learning has increasingly been applied to predict opioid-related harms due to its ability to handle complex interactions and generating actionable predictions. This review evaluated the types and quality of ML methods in opioid safety research, identifying 44 studies using supervised ML through searches of Ovid MEDLINE, PubMed and SCOPUS databases. Commonly predicted outcomes included postoperative opioid use (n = 15, 34%) opioid overdose (n = 8, 18%), opioid use disorder (n = 8, 18%) and persistent opioid use (n = 5, 11%) with varying definitions.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!