Machine learning methods for small data challenges in molecular science

B Dou, Z Zhu, E Merkurjev, L Ke, L Chen… - Chemical …, 2023 - ACS Publications
Small data are often used in scientific and engineering research due to the presence of
various constraints, such as time, cost, ethics, privacy, security, and technical limitations in …

EEG-based emotion classification using stacking ensemble approach

S Chatterjee, YC Byun - Sensors, 2022 - mdpi.com
Rapid advancements in the medical field have drawn much attention to automatic emotion
classification from EEG data. People's emotional states are crucial factors in how they …

Multi-fault detection and classification of wind turbines using stacking classifier

P Waqas Khan, YC Byun - Sensors, 2022 - mdpi.com
Wind turbines are widely used worldwide to generate clean, renewable energy. The biggest
issue with a wind turbine is reducing failures and downtime, which lowers costs associated …

A methodological approach for detecting multiple faults in wind turbine blades based on vibration signals and machine learning

AAF Ogaili, AA Jaber, MN Hamzah - Curved and Layered Structures, 2023 - degruyter.com
Wind turbines generate clean and renewable energy for the international market. The most‎‎
important aspect of wind turbine maintenance is reducing failures, downtime, and operating …

[HTML][HTML] Improved stacked ensemble with genetic algorithm for automatic ecg diagnosis of children living in high-altitude areas

N Zhao, X Li, Y Ma, H Wang, SJ Lee, J Wang - … Signal Processing and …, 2024 - Elsevier
Electrocardiogram (ECG) is a commonly used diagnostic tool in clinical practice that plays a
vital role in the diagnosis and treatment of various heart diseases. Previous studies have …

Augmented data strategies for enhanced computer vision performance in breast cancer diagnosis

A Kaffashbashi, V Sobhani, F Goodarzian… - Journal of Ambient …, 2024 - Springer
Breast cancer remains a formidable global health challenge, exacting a heavy toll on
women's lives and necessitating advanced diagnostic methodologies. This study delves into …

Predicting invasive disease-free survival time in breast cancer patients using semi-supervised graph-based machine learning techniques

R Taimourei-Yansary, M Mirzarezaee… - Soft Computing …, 2022 - scj.kashanu.ac.ir
Breast cancer is currently the most commonly diagnosed cancer and leading cause of
cancer-related deaths among women worldwide. Analyzing the survival time of breast …

[PDF][PDF] Design an Intelligent Multi-agent Computer-aided Model for Recommender Systems

RT Yansari, M Ajoudani… - Journal of Applied …, 2023 - jadsc.aliabad.iau.ir
Increasing the information and services available on the web, providing tools such as
recommender systems to websites and applications for users to find information and …

پیش‌بینی زمان بقا عاری از بیماری تهاجمی در بیماران مبتلا به سرطان پستان با به‌کارگیری روش‌های یادگیری ماشین نیمه نظارتی مبتنی بر گراف

تیموری یانسری, رمضان, میرزارضایی, صادقی… - محاسبات نرم, 2022‎ - scj.kashanu.ac.ir
سرطان پستان در حال حاضر شایع‌ترین سرطان تشخیص‌داده ‌شده و علت اصلی مرگ‌ و میر ناشی از
سرطان در زنان در سراسر جهان است. در سال‌های اخیر در حوزه مطالعات سرطان پستان و روند درمان این …