Results 111 to 120 of about 72,345 (262)

Hybrid PSO-XGBoost Model for Accurate Flood Risk Assessment

Journal of Applied Informatics and Computing
Flood risk prediction is a crucial step in disaster mitigation. This study optimizes the Extreme Gradient Boosting (XGBoost) algorithm using the Particle Swarm Optimization (PSO) method to improve prediction accuracy.
Lailatun Nabilah, Lukman Hakim
doaj   +1 more source

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source

Enhancing Enzyme Activity With Mutation Combinations Guided by Few‐Shot Learning and Causal Inference

Angewandte Chemie, EarlyView.
We present an integrated workflow that predicts activity‐enhancing mutation combinations from minimal experimental data. By proposing in vivo unit yield (yield/expression) as a surrogate for kcat/Km through causal inference, and visualizing local activity landscape, it effectively guides product yield improvement. ABSTRACT Designing enzyme sequences to
Lin Guo, Xiaoguang Yan, Yali Lu, Shengxin Nie, Mingyue Ge, Yukun Li, Weiguo Li, Xiaochun Zhang, Dongmei Liang, Yihan Zhao, Hongxiao Tan, Xiling Chen, Shilong Fan, Yefeng Tang, Jianjun Qiao, Boxue Tian   +15 more
wiley   +2 more sources

Multiclass Classification of Tomato Leaf Diseases Using GLCM, Color, and Shape Feature Extraction with Optimized XGBoost

Journal of Applied Informatics and Computing
Automatic classification of tomato leaf diseases is an essential component in advancing precision agriculture based on artificial intelligence. This study aims to develop a multiclass classification model for tomato leaf diseases by utilizing texture ...
Fransisko Andrade Laiskodat, Majid Rahardi   +1 more
doaj   +1 more source

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

Advanced Intelligent Discovery, EarlyView.
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed, Denis Abu Sammour, Dirk C. Hoffmann, Philipp Sievers, Tobias Bausbacher, Melissa Hahn, Yasemin Ucal, Iris Mildenberger, Christiane A. Opitz, Stefan Schmidt, Michael Platten, Oliver Wasenmüller, Wolfgang Wick, Andreas von Deimling, Tobias Kessler, Carsten Hopf   +15 more
wiley   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

Interpretable artificial intelligence for predicting blood transfusion after surgery for femoral shaft fractures: A retrospective analysis

Indian Journal of Anaesthesia
Background and Aims: Blood transfusions are often necessary in the surgical repair of orthopaedic fractures. However, these transfusions are associated with significant morbidity.
Rameshbabu Manyam, Puneet Gupta, Pengfei Lou, Rui Guo, Andrew Carro, Eric R. Heinz   +5 more
doaj   +1 more source

OXidative Stress PREDictor: A Supervised Learning Approach for Annotating Cellular Oxidative Stress States in Inflammatory Cells

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
OxSpred, an eXtreme‐Gradient‐Boosting‐‐based supervised learning model, accurately annotates oxidative stress in innate immune cells at the single‐cell level, providing interpretable embeddings with significant biological relevance. This innovative tool revolutionizes the understanding of innate immune cell functions during inflammation and enhances ...
Po‐Yuan Chen, Tai‐Ming Ko
wiley   +1 more source

Anomaly detection method for coal mine sensor data

Gong-kuang zidonghua
In response to persistent dense noise anomalies, instantaneous impulse anomalies, and missing anomalies in sensor data caused by the complex underground environment of coal mines, existing data anomaly detection methods have difficulty adapting to ...
YANG Yuqi, FU Xiang, ZHANG Zhixing, YAN Ming, LI Haojie, LIU Bin, NIU Penghao, HUANG Jinyu   +7 more
doaj   +1 more source

Data‐Driven Design of Bimodal Networked Dielectric Elastomers for High‐Performance Artificial Muscles

Advanced Intelligent Systems, EarlyView.
A data‐efficient artificial intelligence‐assisted framework, which integrates experimental data with machine learning, is developed for the design of bimodal networked dielectric elastomers (DEs) as advanced artificial muscles. It adopts neural networks to predict DEs’ mechanical properties and support vector machines to classify electromechanical ...
Ofoq Normahmedov, Hanzhi Ma, Junbo Peng, Huifeng Dong, Jiangshan Zhuo, Mengke Shi, Lvting Wang, Shengchao Jiang, Ye Shi   +8 more
wiley   +1 more source