Machine learning prediction of dioxin lipophilicity and key feature ...
Feb 1, 2025 · Machine learning methods enable rapid and effective prediction of molecular properties, accurately identifying relationships between molecular structure and properties. This approach saves …
Machine learning-driven risk prediction and feature identification …
Jul 15, 2025 · Machine learning-driven risk prediction and feature identification for major depressive disorder and its progression: an exploratory study based on five years of longitudinal data from the …
Identification of key feature variables and prediction of harmful algal ...
Jul 1, 2025 · The data preparation module involves data collection, preprocessing, and feature comparison to ensure high-quality input for model training. In the model development and …
Machine learning for subsurface geological feature identification …
Oct 1, 2024 · The capabilities of big data processing, automatic feature learning, and nonlinear relationship modeling that ML holds provide a new perspective for geophysical researchers in …
Abstract 1123: Machine learning classifier for cancer type ...
4 days ago · Our cfDNA-based machine learning classifier provides a robust, non-invasive approach for accurate cancer tissue-of-origin identification. Integrating 11 distinct cfDNA-derived fragmentomic, …
Machine learning‐based genetic feature identification and fatigue …
Jun 21, 2021 · The development of machine learning (ML) provides an effective way to solve complex process problems, and it offers significant advantages in identifying key features of fatigue life under …
Multi-stage damage identification method for PC structures based on ...
Nov 1, 2024 · Efficient and accurate damage identification methods are great significant for ensuring the structural safety. This study proposes a multi-stage damage identification method for prestressed …
Machine learning assisted nanozyme sensor array for accurate ...
Sep 15, 2025 · Notably, the integration of multiple machine learning algorithms with the sensor array enabled accurate identification and prediction of five flavonoids in licorice, chrysanthemum, and …
A Machine-Learning-Based Approach to Critical Geometrical Feature ...
Sep 16, 2022 · This work investigates the opportunity to use machine learning algorithms in order to identify hard-to-manufacture geometrical features. The segmentation of these features from the main …
Identification of optimal metal-organic frameworks by machine learning ...
Apr 1, 2022 · A novel integrated machine learning (ML) framework, consisting of structure decomposition, feature integration and predictive modeling, is proposed to correlate MOF structures …