Results 261 to 270 of about 85,077 (292)

Formation permeability estimation using mud loss data by deep learning. [PDF]

Sci Rep
Abdollahfard Y, Mirabbasi SM, Ahmadi M, Hemmati-Sarapardeh A, Ashoorian S.   +4 more
europepmc   +1 more source

AI‐Enhanced Surface‐Enhanced Raman Scattering for Accurate and Sensitive Biomedical Sensing

Advanced Intelligent Discovery, EarlyView.
AI‐SERS advances spectral interpretation with greater precision and speed, enhancing molecular detection, biomedical analysis, and imaging. This review explores its essential contributions to biofluid analysis, disease identification, therapeutic agent evaluation, and high‐resolution biomedical imaging, aiding diagnostic decision‐making.
Seungki Lee, Rowoon Park, Ho Sang Jung
wiley   +1 more source

Hardware-Accelerated Non-Contact System for Sleep Disorder Monitoring and Analysis. [PDF]

Sensors (Basel)
Sravanthi M, Gunturi SK, Chinnaiah MC, Divya Vani G, Basha M, Janardhan N, Hari Krishna D, Dubey S.   +7 more
europepmc   +1 more source

Piezoelectric Origami Metamaterials for Enhanced Handwriting Recognition and Trajectory Tracking

Advanced Intelligent Discovery, EarlyView.
This study introduces origami metamaterials inspired by Kresling piezoelectric generators to enhance biometric authentication and handwriting trajectory recognition. Overcoming sensor limitations in conventional devices, the design enables multichannel data acquisition with fewer sensors, utilizing machine learning to accurately identify content ...
Yinzhi Jin, Ting Tan, Zhimiao Yan
wiley   +1 more source

An adaptive feedback system for the improvement of learners. [PDF]

Sci Rep
Qadir HM, Khan RA, Rasool M, Sohaib M, Shah MA, Hasan MJ.   +5 more
europepmc   +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

Dry sliding tribological characteristics evaluation and prediction of TiB₂-CDA/Al6061 hybrid composites exercising machine learning methods. [PDF]

Sci Rep
Aherwar A, Ahirwar A, Pathak VK.
europepmc   +1 more source

DTreePred: an online viewer based on machine learning for pathogenicity prediction of genomic variants. [PDF]

BMC Bioinformatics
Gomes DHF, Medeiros IG, Petta TB, Stransky B, de Souza JES.   +4 more
europepmc   +1 more source

Risk prediction and effect evaluation of complicated appendicitis based on XGBoost modeling. [PDF]

BMC Gastroenterol
Chen S, Xia J, Xu B, Huang Y, Teng M, Pan J.   +5 more
europepmc   +1 more source

Application of Machine Learning in Amorphous Alloys. [PDF]

Materials (Basel)
Zhang L, Zhang H, Ji B, Liu L, Liu X, Chen D.   +5 more
europepmc   +1 more source