Results 241 to 250 of about 3,103,450 (291)

Predicting Atrial Fibrillation Relapse Using Bayesian Networks: Explainable AI Approach. [PDF]

JMIR Cardio
Alves JM, Matos D, Martins T, Cavaco D, Carmo P, Galvão P, Costa FM, Morgado F, Ferreira AM, Freitas P, Dias CC, Rodrigues PP, Adragão P.   +12 more
europepmc   +1 more source

Large‐Scale Machine Learning to Screen for Small‐Molecule Senolytics

Advanced Intelligent Discovery, EarlyView.
A consistent workflow underpins all experiments in this study. A dedicated model‐selection dataset first identifies optimal hyperparameters for each algorithm. Models are then trained and rigorously evaluated on independent sets of molecules using the senolytic ratio SR. Comprehensive hyperparameter exploration across SMILES representations, task types,
Alexis Dougha, Jesus Gil, Pedro J. Ballester   +2 more
wiley   +1 more source

Exploring stroke risk factors in different genders using Bayesian networks: a cross-sectional study involving a population of 134,382. [PDF]

BMC Public Health
Linghu L, Huang Y, Qiu L, Wang X, Zhang J, Ma L, Li C, Wang L.   +7 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

Using Bayesian Networks to Predict Urgent Care Visits in Patients Receiving Systemic Therapy for Non-Small Cell Lung Cancer. [PDF]

JCO Clin Cancer Inform
Gonzalez BD, Li X, Gudenkauf LM, Pullukkara JJ, Oswald LB, Hoogland AI, Le T, El Naqa I, Saltos AN, Haura EB, Luo Y.   +10 more
europepmc   +1 more source

Generative and Experimental Validation of High Refractive Index Polymers via Domain Knowledge Approach with Small Data

Advanced Intelligent Discovery, EarlyView.
This research demonstrates that the combination of domain knowledge–based multiple regression, multi‐objective Bayesian optimization, and generative models is a suitable prediction tool for candidates of high refractive index polymers, even with the constraints in the model trained on limited data. The experimental validation can reproduce the proposed
Takuya Yokoo, Seigo Watanabe, Hana Matsunaga, Kenichi Oyaizu   +3 more
wiley   +1 more source

General framework of nonlinear factor interactions using bayesian networks for risk analysis applied to road safety and public health. [PDF]

Sci Rep
Carrodano C.
europepmc   +1 more source

Sensitivity analysis of unsafe behaviors in the spinning and weaving factories: Exploring the association with burnout and resilience using Bayesian networks. [PDF]

PLoS One
Azimi R, Al Sulaie S, Yazdanirad S, Khoshakhlagh AH, Cousins R, Kazemian F.   +5 more
europepmc   +1 more source

Causal mapping of psychological and occupational risk factors for suicidal ideation in psychiatric nurses using Bayesian networks: A multicenter cross-sectional study. [PDF]

PLoS One
Wang M, Yan Y, Yang W, He R, Zhao L, Dou Y, Tao Y, Yang X, Xiang Q, Ma X.   +9 more
europepmc   +1 more source

Dynamic Bayesian Networks, Elicitation, and Data Embedding for Secure Environments. [PDF]

Entropy (Basel)
Drury K, Smith JQ.
europepmc   +1 more source