AI-Driven Hybrid Detection and Classification Framework for Secure Sleep Health IoT Networks. [PDF]
Valsalan P, Siddiqui MM.
europepmc +1 more source
Machine‐Learning Microfluidic Minute‐Scale Microorganism Metrics Monitoring(M6)
ABSTRACT On‐site monitoring of microorganisms remains challenging because of low concentrations, strong background interference, and dynamic aerosol diffusion, particularly for aerosol‐transmitted pathogens. Here, we report a rapid detection platform that integrates a Puri‐focusing microfluidic chip, electrochemical impedance spectroscopy (EIS), and ...
Ning Yang +14 more
wiley +1 more source
Efficient EEG channel-and-frequency-band selection for epileptic seizure classification using multi-objective optimization. [PDF]
Chen W, Lei X, Guo H, Zhuang L.
europepmc +1 more source
An Integrated NLP‐ML Framework for Property Prediction and Design of Steels
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju +5 more
wiley +1 more source
Synergistic ANN-GA-CFD framework for high-performance Savonius wind turbine optimization with experimental validation. [PDF]
Sehsah HM +3 more
europepmc +1 more source
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source
Optimizing Budget Allocation for Digital Health Investments Using Metaheuristic Algorithms: A Cost-Impact Analysis for Public Health Systems. [PDF]
Dayi F +4 more
europepmc +1 more source
Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu +4 more
wiley +1 more source
Multi-omics and artificial intelligence for precision drug discovery and potential clinical applications. [PDF]
Liu Y, Zhu K, Peng W, Liu Z, Mao X.
europepmc +1 more source

