Results 131 to 140 of about 157,640 (328)

Autonomous AI‐Driven Design for Skin Product Formulations

Advanced Intelligent Discovery, EarlyView.
This review presents a comprehensive closed‐loop framework for autonomous skin product formulation design. By integrating artificial intelligence‐driven experiment selection with automated multi‐tiered assays, the approach shifts development from trial‐and‐error to intelligent optimisation.
Yu Zhang, Yongrui Xiao, Chunlin Chen, Dimitrios Tsaoulidis, Kai Yang, Tao Chen   +5 more
wiley   +1 more source

Modeling hierarchical relationships in epidemiological studies: a Bayesian networks approach [PDF]

Hierarchical relationships between risk factors are seldom taken into account in epidemiological studies though some authors stressed the importance of doing so, and proposed a conceptual framework in which each level of the hierarchy is modeled ...
Nguefack-Tsague, Georges, Zucchini, Walter   +1 more
core   +1 more source

Determining factors associated with cholera disease in Ethiopia using Bayesian hierarchical modeling. [PDF]

BMC Public Health, 2022
Letta TT, Belay DB, Ali EA.
europepmc   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

Bayesian geostatistical modeling outperforms machine learning for mapping carbon stocks from Sentinel-2 data in plantation-forest landscapes of Zimbabwe’s Eastern Highlands

Frontiers in Forests and Global Change
IntroductionAccurate, spatially explicit estimates of carbon stocks in plantation forests are essential for sustainable management and credible climate-change mitigation, yet plantation mosaics often exhibit strong spatial structure that can reduce the ...
Tsikai Solomon Chinembiri, Onisimo Mutanga   +1 more
doaj   +1 more source

Data used in generation of results in 'Bias Correction of Climate Models using a Bayesian Hierarchical Model' J.Carter et. al.

, 2023
Jeremy Carter
openalex   +1 more source

Illustrating a Species Sensitivity Distribution for Nano- and Microplastic Particles Using Bayesian Hierarchical Modeling. [PDF]

Environ Toxicol Chem, 2022
Takeshita KM, Iwasaki Y, Sinclair TM, Hayashi TI, Naito W.   +4 more
europepmc   +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

What Is the Added Benefit of Combining Cognitive Behavioral Therapy and Selective Serotonin Reuptake Inhibitors in Youth with Obsessive Compulsive Disorder? A Bayesian Hierarchical Modeling Meta-Analysis. [PDF]

J Child Adolesc Psychopharmacol, 2023
Mendez EM, Dahlsgaard KK, Hjelmgren JM, Mills JA, Suresh V, Strawn JR.   +5 more
europepmc   +1 more source

i‐Tac: Inverse Design of 3D‐Printed Tactile Elastomers with Tuneable Optical and Mechanical Properties

Advanced Intelligent Systems, EarlyView.
Inspired by the multi‐tissue architecture of the human fingertip dermis (A), this work introduces a mixture design using three PolyJet materials (AC/TM/GM) to expand the achievable elastomer property space (B). An inverse design pipeline (i‐Tac) is developed to map target optical/mechanical requirements to optimal material compositions (C), enabling ...
Wen Fan, Dandan Zhang
wiley   +1 more source