This is an important work implementing data mining methods on IMC data to discover spatial protein patterns related to the triple-negative breast cancer patients' chemotherapy response. The evidence ...

Abstract: Fuzzy classification models are important for handling uncertainty and heterogeneity in high-dimensional data. Although recent fuzzy logistic regression approaches have demonstrated ...

This set of notebooks enables the analysis of comorbidities associated with male infertility using structured EHR data. First, we identified nonoverlapping patients with male infertility and patients ...

Abstract: The importance of features interactions for classification tasks between two classes is proven by the abundance of high-performance machine learning methods using them. In this paper, we ...

Objective: There is limited study on predictive models for live births in patients with polycystic ovarian syndrome (PCOS). The study aimed to develop and validate a nomogram for predicting live ...

Learn how to implement Logistic Regression from scratch in Python with this simple, easy-to-follow guide! Perfect for beginners, this tutorial covers every step of the process and helps you understand ...

1 Department of Computer Science, Nagoya Institute of Technology, Aichi, Japan 2 RIKEN Center for Advanced Intelligence Project, Tokyo, Japan In recent years, a learning method for classifiers using ...

article{londschien2025, title={Domain Generalization and Adaptation in Intensive Care with Anchor Regression}, author={Londschien, Malte, Burger, Manuel, R{\"a}tsch ...

ABSTRACT: The Efficient Market Hypothesis postulates that stock prices are unpredictable and complex, so they are challenging to forecast. However, this study demonstrates that it is possible to ...