Results 131 to 140 of about 288,297 (331)

Artificial Intelligence for Bone: Theory, Methods, and Applications

open access: yesAdvanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan   +3 more
wiley   +1 more source

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

open access: yesAdvanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu   +4 more
wiley   +1 more source

DATA WAREHOUSE - STRATEGIC ADVANTAGE [PDF]

open access: yesIssues in Information Systems, 2001
Sudesh Duggal, Inna Pylyayeva
doaj  

A Machine Learning Model for Interpretable PECVD Deposition Rate Prediction

open access: yesAdvanced Intelligent Discovery, EarlyView.
This study develops six machine learning models (k‐nearest neighbors, support vector regression, decision tree, random forest, CatBoost, and backpropagation neural network) to predict SiNx deposition rates in plasma‐enhanced chemical vapor deposition using hybrid production and simulation data.
Yuxuan Zhai   +8 more
wiley   +1 more source

Knowledge Management Process for Air Quality Systems based on Data Warehouse Specification

open access: diamond, 2021
Mohamed Saifeddine Hadj Sassi   +3 more
openalex   +1 more source

A Comprehensive Assessment and Benchmark Study of Large Atomistic Foundation Models for Phonons

open access: yesAdvanced Intelligent Discovery, EarlyView.
We benchmark six large atomistic foundation models on 2429 crystalline materials for phonon transport properties. The rapid development of universal machine learning potentials (uMLPs) has enabled efficient, accurate predictions of diverse material properties across broad chemical spaces.
Md Zaibul Anam   +5 more
wiley   +1 more source

Data Warehouse

open access: yesJournal of Japan Society for Fuzzy Theory and Systems, 1998
openaire   +3 more sources

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