Predictive Value of Different Machine Learning Models for Clinical Pregnancy Outcomes in Patients with Polycystic Ovary Syndrome Undergoing IVF/ICSI Treatment

Machine Learning for Predictive Modeling and Simulation of Urban Renewal Using Multi-Source Spatial Data

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The predictive value of machine learning models based on RANKL and OPG for the risk of bone loss in patients with ulcerative colitis

Renyu Liang

Also available via: European Organization for Nuclear Research

Feature Importance and Growth Rate Prediction in SiC PVT Processes through Advanced Machine Learning Models

Amir Reza Ansari Dezfoli

Silicon carbide is a key wide-bandgap semiconductor material for next-generation power electronics, yet the Physical Vapor Transport (PVT) method used for bulk crystal growth remains constrained by complex thermal-chemical interactions and low growth rates. This study develops a…Read more

Also available via: European Organization for Nuclear Research

Comparative Analysis of Machine Learning Classification Algorithms and Hybrid Models for Student Performance Prediction

Ms. Pooja C. Soni, Dr. Hetal R. Modi, PC Negi

This study focuses on the analysis and comparison of machine learning classification algorithms and hybrid machine learning models for predicting student academic performance. Educational Data Mining techniques are used to extract meaningful insights from student datasets. Variou…Read more

An Explainable Machine Learning Model and Bedside Nomogram Support Hemodialysis Decision-Making in Lithium Poisoning

Kamran Rezaei, Shahin Shadnia, Babak Mostafazadeh, Mitra Rahimi, Peyman erfantalabevini, Seyed Masoud Hosseini, et al.

The python codes for evaluation of a dataset containing lithium poisoning patients' data. Four Machine Learning models were used (Elastic-Net logistic regression (LR), linear support vector machine (SVM), shallow artificial neural network (ANN), and constrained Random Forest). Ea…Read more

Also available via: European Organization for Nuclear Research

Financial data source preparation and analysis as the initial stage of stochastic time series modeling by machine learning techniques

Yurchenko Yuriy, Oleksandr Zakovorotnyi

Proceedings of the Scientific Conference "The 13th International Scientific and Practical Online Conference of Young Scientists and Students ‘Contemporary Problems of Automation and Control’".The conference talk presents a structured approach to preparing and analyzing financial…Read more

Also available via: European Organization for Nuclear Research