Results 41 to 50 of about 52,163 (250)

Maternal recall of breastfeeding duration twenty years after delivery

BMC Medical Research Methodology, 2012
Background Studies on the health benefits from breastfeeding often rely on maternal recall of breastfeeding. Although short-term maternal recall has been found to be quite accurate, less is known about long-term accuracy.
Natland Siv Tone, Andersen Lene Frost, Nilsen Tom Ivar Lund, Forsmo Siri, Jacobsen Geir W   +4 more
doaj   +1 more source

High‐Throughput Data Generation and Transfer Learning Enabled Microstructure‐Property Integrated Design of Nickel‐Based Powder Metallurgy Superalloy

Advanced Science, EarlyView.
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li, Hongtao Zhang, Zichao Peng, Yuheng Zhang, Qian Lv, Yihuan Cao, Xuqing Wang, Huadong Fu, Jianxin Xie   +8 more
wiley   +1 more source

Code-free automated machine learning for OCT-based classification of vitreoretinal interface diseases

International Journal of Retina and Vitreous
Background Differentiation of vitreoretinal interface disorders on optical coherence tomography (OCT) relies on expert interpretation and can be challenging in borderline cases.
Lorenzo Ferro Desideri, Enrico Bernardi, Carla Troyas, Yousif Subhi, Mehmet Cem Sabaner, Martin Zinkernagel, Rodrigo Anguita   +6 more
doaj   +1 more source

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

Advanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang, Waleed Mohammed, Dierk Raabe   +2 more
wiley   +1 more source

Data Leakage and Deceptive Performance: A Critical Examination of Credit Card Fraud Detection Methodologies

Mathematics
This study critically examines the methodological rigor in credit card fraud detection research, revealing how fundamental evaluation flaws can overshadow algorithmic sophistication.
Khizar Hayat, Baptiste Magnier
doaj   +1 more source

stMixer for Scalable Mosaic Integration and Label Transfer in Spatial Histology and Multi‐Omics

Advanced Science, EarlyView.
stMixer is an unsupervised framework for scalable integration and label transfer across spatial histology and multi‐slide multi‐omics data with incomplete modality overlap. It combines self‐looped cross‐attention, multimodal metric learning, and graph‐guided cluster voting to align heterogeneous sections, correct batch effects, and propagate ...
Qixing Yang, Yan Wang, Luonan Chen, Chunman Zuo   +3 more
wiley   +1 more source

Classification of Heavy Metal-Indicated Soil Types Using Decision Tree Algorithm and IoT-Based pH-Moisture Sensors

Jurnal Jaringan Telekomunikasi
This study implements the Decision Tree algorithm for the classification of three soil types: Paddy Field, Well Excavation, and Lapindo Mud. The classification is performed based on two key parameters that influence soil characteristics: pH and Humidity.
Dhea Adrika Zahro Asyhari, Hudiono Hudiono, Hendro Darmono   +2 more
doaj   +1 more source

Automated Extraction of Multicomponent Alloy Data Using Large Language Models for Sustainable Design

Advanced Science, EarlyView.
A large language model (LLM) based pipeline is developed to automatically extract a comprehensive and accurate multicomponent alloy database from literature corpus. The extracted dataset is integrated with sustainability indicators to identify potential alloys that outperform existing industrial benchmark materials in terms of both performance and ...
Aravindan Kamatchi Sundaram, Mohit Chakraborty, Sai Mani Kumar Devathi, B. Pabitramohan Prusty, Rohit Batra   +4 more
wiley   +1 more source

Transfer Learning With CLIP for Intelligent Concrete Crack Detection in Structural Health Monitoring

Shock and Vibration
Automated detection of surface cracks in concrete structures is a fundamental requirement for effective structural health monitoring and preventive maintenance.
Md. Siam Ansary
doaj   +1 more source

Predicting Respiratory Conditions Using Random Forest and XGBoost

Journal of Information Systems and Informatics
This study examines the performance of Random Forest and XGBoost in predicting the diagnosis and severity of respiratory diseases using a simulated dataset of 2,000 patient records. The models were tested on two classification tasks: identifying disease
Dhiyaussalam Dhiyaussalam, Ahmad Yusuf, Isna Wardiah, Nitami Lestari Putri   +3 more
doaj   +1 more source