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Data-driven performance prediction of polymer solar cells using multi-layer perceptron with Bayesian hyperparameter tuning

Sun Ping • Materials Research Express (2026)

Polymer solar cells (PSCs) rely on labor-intensive trial-and-error experiments to optimize power conversion efficiency (PCE), due to complex coupling of molecular electronic properties, blend morphology and fabrication parameters. This work...

DOAJ Open Access (DOAJ) DOI: 10.1088/2053-1591/aeaacc

Machine learning insight in quality control and maintenance management of drilling mud pumps

Xiaoming Wu, Jingxuan Chang, Chengcheng Long, Hamzeh Ghorbani • Journal of Big Data (2026)

Abstract This study proposes a machine learning-based framework for predictive maintenance and quality control of drilling mud pumps, targeting critical operational challenges such as equipment failure, downtime, and high maintenance costs....

DOAJ Open Access (DOAJ) DOI: 10.1186/s40537-026-01475-9

Development and validation of a predictive model for diabetic peripheral neuropathy with type 2 diabetes mellitus in Xinjiang, China

Asiguli Adili, Maihesumu Aikemu, Karanvir Singh Rana, Yihan Wei et al. • Scientific Reports (2025)

Abstract This study aims to identify risk factors associated with diabetic peripheral neuropathy (DPN) in patients with type 2 diabetesmellitus (T2DM) and to develop a predictive model to support clinical decision-making. A total of 1,001 p...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-19922-7

Machine learning in pain research

Jörn Lötsch, Alfred Ultsch • Pain (2017)

1. Introduction Pain and pain chronification are incompletely understood and unresolved medical problems that continue to have a high prevalence.14 It has been accepted that pain is a complex phenomenon.2,32,72 Contemporary methods of compu...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1097/j.pain.0000000000001118 PMC: 5895117

Dynamic Monitoring of Thyroid-Stimulating Hormone Receptor Antibody and Extraocular Muscle Thickness: A Clinical Risk Stratification Model for Recurrence Risk Post-Glucocorticoid Therapy in TED Patients

Li Y, Yang X, Hu S • International Journal of General Medicine (2026)

Yaling Li, Xiuhong Yang, Shuli Hu Department of Intensive Care Unit, Wuhan No. 1 Hospital, Wuhan, 430022, People’s Republic of ChinaCorrespondence: Shuli Hu, Department of Intensive Care Unit, Wuhan No. 1 Hospital, No. 215 Zhongshan Avenue,...

DOAJ Open Access (DOAJ)

Machine Learning for Stock Selection

Keywan Christian Rasekhschaffe, Robert C. Jones • Financial Analysts Journal (2019)

Machine learning is an increasingly important and controversial topic in quantitative finance. A lively debate persists as to whether machine learning techniques can be practical investment tools. Although machine learning algorithms can un...

OPENALEX DOI: https://doi.org/10.1080/0015198x.2019.1596678

Overfitting and undercomputing in machine learning

Thomas G. Dietterich • ACM Computing Surveys (1995)

suggests a reasonable line of research: find algorithms that can search the hypothesis class better. Hence, there is been extensive research in applying second-order methods to fit neural networks and in conducting much more thorough search...

OPENALEX Open Access DOI: https://doi.org/10.1145/212094.212114

Elements of Machine Learning

Pat Langley B (1995)

Elements of Machine Learning by Pat Langley Preface 1. An overview of machine learning 1.1 The science of machine learning 1.2 Nature of the environment 1.3 Nature of representation and performance 1.4 Nature of the learning component 1.5 F...

OPENALEX

Taxonomy-based data representation for data mining: an example of the magnitude of risk associated with H. pylori infection

Inese Polaka, Danute Razuka-Ebela, Jin Young Park, Marcis Leja • BioData Mining (2021)

Abstract Background The amount of available and potentially significant data describing study subjects is ever growing with the introduction and integration of different registries and data banks. The single specific attribute of these data...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13040-021-00271-w

Application of artificial intelligence in gastroenterology

Young Joo Yang, Chang Seok Bang • World Journal of Gastroenterology (2019)

Artificial intelligence (AI) using deep-learning (DL) has emerged as a breakthrough computer technology. By the era of big data, the accumulation of an enormous number of digital images and medical records drove the need for the utilization...

OPENALEX cc-by-nc DOI: https://doi.org/10.3748/wjg.v25.i14.1666 PMC: 6465941