Evaluation of feature selection methods for preserving machine learning performance in the presence of temporal dataset shift in clinical medicine
Background Temporal dataset shift can cause degradation in model performance as
discrepancies between training and deployment data grow over time. The primary objective …
discrepancies between training and deployment data grow over time. The primary objective …
Beyond chemical language: A multimodal approach to enhance molecular property prediction
We present a novel multimodal language model approach for predicting molecular
properties by combining chemical language representation with physicochemical features …
properties by combining chemical language representation with physicochemical features …
To Share or Not to Share: Understanding and Modeling Individual Disclosure Preferences in Recommender Systems for the Workplace
Newly-formed teams often encounter the challenge of members coming together to
collaborate on a project without prior knowledge of each other's working and communication …
collaborate on a project without prior knowledge of each other's working and communication …
Robust Feature Selection for BP Estimation in Multiple Populations: Towards Cuffless Ambulatory BP Monitoring
Current blood pressure (BP) estimation methods have not achieved an accurate and
adaptable approach for ambulatory diagnosis and monitoring applications of populations at …
adaptable approach for ambulatory diagnosis and monitoring applications of populations at …
Interpretable data-driven approach based on feature selection methods and GAN-based models for cardiovascular risk prediction in diabetic patients
D Chushig-Muzo, H Calero-Díaz… - IEEE …, 2024 - ieeexplore.ieee.org
Noncommunicable diseases (NCDs) are the leading cause of morbidity and mortality
worldwide. Cardiovascular diseases (CVDs) and diabetes are the most prevalent NCDs …
worldwide. Cardiovascular diseases (CVDs) and diabetes are the most prevalent NCDs …
Score-based causal feature selection for cancer risk prediction
S Huang, Q Li, L Wang, Y Wang… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
The primary goal of cancer risk prediction is to find dominant features, with each being
responsible for cancer diagnosis. As a result, selected feature sets often converge to …
responsible for cancer diagnosis. As a result, selected feature sets often converge to …
Robust Feature Selection for Continuous BP Estimation in Multiple Populations: Towards Cuffless Ambulatory BP Monitoring
Current blood pressure (BP) estimation methods have not achieved an accurate and
adaptable approach for application in populations at risk of cardiovascular disease, with …
adaptable approach for application in populations at risk of cardiovascular disease, with …
[PDF][PDF] SHAPLEY VALUES AS A GENERIC APPROACH TO INTERPRETABLE FEATURE SELECTION
I Trotskii - 2023 - trepo.tuni.fi
Supervisor: Frank Emmert-Streib Tampere University Master's Degree Programme in
Robotics and Artificial Intelligence October 2023 The Shapley value is one of the most …
Robotics and Artificial Intelligence October 2023 The Shapley value is one of the most …
Analysis of Markov Blanket Based Feature Ranking for Android Malware Detection
Y Yusfrizal, A Syahputra, Y Tanjung - Journal of Artificial …, 2024 - ioinformatic.org
The ubiquity of Android applications in our daily lives has brought forth an indispensable
need for robust app security mechanisms. Malware-infested applications not only jeopardize …
need for robust app security mechanisms. Malware-infested applications not only jeopardize …
Machine Learning Soft Voting Algorithm for Prediction and Detection of Nonalcoholic Fatty Liver Disease
G Cao, H Zhang - 2022 - researchsquare.com
Nonalcoholic fatty liver disease (NAFLD) is one of the most commonly diagnosed chronic
liver diseases in the world and has become an essential public health problem. Introduction …
liver diseases in the world and has become an essential public health problem. Introduction …