Explainable machine learning and feature engineering applied to nanoindentation data by C.O.W. Trost, S. Žák, S. Schaffer, L. Walch, J. Zitz, T. Klünsner, H. Leitner, L. Exl, M.J. Cordill

“…The resulting dataset was used to train and benchmark supervised (classification) and unsupervised (clustering) machine learning models, showing that feature engineering was more impactful than model selection and hyperparameter tuning, increasing the prediction quality in all studied models. …”
Get full text

Improving data processing in medical education through machine learning by N. Shyndaliyev, A. Orynbayeva, K. Shadinova, A. Barakova, N. Nurmukhanbetova

“…The exponential growth of biomedical data coupled with advances in machine learning (ML) has created opportunities for more precise diagnosis, enhanced treatment planning, and improved patient management. …”
Get full text

Quantitative analysis of EXAFS data sets using deep reinforcement learning by Eun-Suk Jeong, In-Hui Hwang, Sang-Wook Han

Get full text

Quantum Machine Learning for Identifying Transient Events in X-Ray Light Curves by Taiki Kawamuro, Shinya Yamada, Shigehiro Nagataki, Shunji Matsuura, Yusuke Sakai, Satoshi Yamada

Get full text

Applications of Machine Learning and Remote Sensing in Soil and Water Conservation by Ye Inn Kim, Woo Hyeon Park, Yongchul Shin, Jin-Woo Park, Bernie Engel, Young-Jo Yun, Won Seok Jang

Subjects: “…machine learning…”
Get full text

End-to-End Architecture for Real-Time IoT Analytics and Predictive Maintenance Using Stream Processing and ML Pipelines by Ouiam Khattach, Omar Moussaoui, Mohammed Hassine

“…A modular machine-learning pipeline handles automated data preprocessing, training, and evaluation across various models. …”
Get full text

Distributed energy sharing algorithm for Micro Grid energy system based on cloud computing by Wenwei Su, Yan Shi

Subjects: Get full text

Consumer Behaviour: Analysing Marketing Campaigns through Recommender Systems and Statistical Techniques

Subjects: “…apriori; decision analytics; machine learning; marketing data; recommendation system…”
Get full text

Groundwater estimation and determination of its probable recharge source in the Lower Swat District, Khyber Pakhtunkhwa, Pakistan, using analytical data and multiple machine learning models by Imran Ahmad, Ibrar Ul Haq, Mansoor Ahmad, Iram Gul, Mursaleen Khan, Khushnuma Khushnuma, Ubaid Ullah, Maqsood Ur Rehman, Mohamed Metwaly

“…It aims to identify recharge sources using a combination of analytical data and advanced machine learning (ML) algorithms. …”
Get full text

Revolutionizing healthcare data analytics with federated learning: A comprehensive survey of applications, systems, and future directions by Nisha Thorakkattu Madathil, Fida K. Dankar, Marton Gergely, Abdelkader Nasreddine Belkacem, Saed Alrabaee

“…Federated learning (FL)–a distributed machine learning that offers collaborative training of global models across multiple clients. …”
Get full text

Survival analysis for sepsis patients: A machine learning approach to feature selection and predictive modeling by Kaida Cai, Xiaofang Yang, Zhengyan Wang, Wenzhi Fu, Hanwen Liu, Fatemeh Mahmoudi

Subjects: “…Machine learning…”
Get full text

Data-Driven and Machine-Learning-Based Real-Time Viscosity Measurement Using a Compliant Mechanism by Nitin V. Satpute, Pratibha Mahajan, Abhishek M. Bhagawati, Keyur G. Kulkarni, Kaustubh M. Utpat, Ganesh D. Korwar, Jagadish V. Tawade, Joanna Iwaniec, Krzysztof Kołodziejczyk

Get full text

A systematic review of machine learning-based remote sensing data analysis for geological and mined materials characterisation by Sureka Thiruchittampalam, Bikram Pratap Banerjee, Nancy F Glenn, Simit Raval

“…To explore current practices and the application of machine learning in interpreting complex imaging data for mine material characterisation, a review of 92 studies from 2004 to 2024 was conducted. …”
Get full text

A New Machine Learning Algorithm for Regional Low-Carbon Economic Development Analysis Based on Data Mining by Xinlei Liu

Get full text

Biomarker discovery studies for patient stratification using machine learning analysis of omics data: a scoping review by Rita Banzi, Jacques Demotes, Paula Garcia, Enrico Glaab, Armin Rauschenberger, Chiara Gerardi

“…These include study design choices to ensure sufficient statistical power for model building and external testing, suitable combinations of non-targeted and targeted measurement technologies, the integration of prior biological knowledge, strict filtering and inclusion/exclusion criteria, and the adequacy of statistical and machine learning methods for discovery and validation.Conclusions While most clinically validated biomarker models derived from omics data have been developed for personalised oncology, first applications for non-cancer diseases show the potential of multivariate omics biomarker design for other complex disorders. …”
Get full text

A Comparative Analysis of Machine Learning and Pedotransfer Functions Under Varying Data Availability in Two Greek Regions by Panagiotis Tziachris, Panagiota Louka, Eirini Metaxa, Miltiadis Iatrou, Konstantinos Tsiouplakis

Get full text

A comparative analysis of machine learning-based methods for impervious surface mapping using SAR and optical data by Siqi He, Lihong Zhu, Yiman Li, Qing Xia, Qiong Zheng, Zheng Wang, Xinyu Zou

Get full text

Multicenter comparative analysis of local and aggregated data training strategies in COVID-19 outcome prediction with Machine learning. by Carine Savalli, Roberta Moreira Wichmann, Fabiano Barcellos Filho, Fernando Timoteo Fernandes, Alexandre Dias Porto Chiavegatto Filho, IACOV-BR Network

“…Our study brings to light an important concern about the impact of grouping data from different hospitals in predictive machine learning models. …”
Get full text

Correction: Predicting the risk of depression in older adults with disability using machine learning: an analysis based on CHARLS data by Tongtong Jin, Ayitijiang· Halili

Get full text

The Effect of Various Text Representation Methods for Sentiment Analysis on Movie Review Data with Different Machine Learning Methods by Veysel Göç, Muhammet Sinan Başarslan

“…In this study, we explore the potential of machine learning (ML) models after different text representation methods on the balanced IMDB dataset, which is widely regarded as a gold standard in sentiment analysis, one of the Natural Language processing (NLP) tasks. …”
Get full text