Results 211 to 220 of about 520,634 (314)

Quantitative adverse outcome pathway modeling for cigarette smoke-inducible airway mucus hypersecretion. Part 2: Bayesian network modeling for probabilistic risk estimation [PDF]

Shigeaki Ito, Sakuya Ichikawa, Risa Matsumoto, Shugo Muratani, Keigo Sano, A. Mori, Kazuo Erami   +6 more
openalex   +1 more source

SmartDetectAI: An AI‐Powered Web App for Real‐Time Colorimetric Detection of Heavy Metals in Water

Advanced Intelligent Systems, EarlyView.
SmartDetectAI integrates silver nanoparticle‐based colorimetric sensing with an AI‐powered web app for rapid, on‐site detection of toxic heavy metals in water. By combining aggregation‐driven optical changes with machine learning analysis of red ‐ green ‐ blue values, the platform achieves portable, low‐cost, and accurate monitoring of Hg‐ and Cd‐based
Nishat Tasnim, Mirza M. A. Tunur, Fahad Arefin, Shahad Saroar, Md. Wahadoszamen, Taslim Ur Rashid, Aminul I. Talukder, Md. Nurul Amin, Mahmudur Rahman, Ahsan Habib   +9 more
wiley   +1 more source

Dynamic Bayesian network analysis of the social determinants of mental health. [PDF]

PNAS Nexus
Skinner A, Li I, Varidel M, Iorfino F, Occhipinti JA, Song YJC, Chong MK, Hickie IB.   +7 more
europepmc   +1 more source

Biomarker‐Agnostic Detection of Ovarian Cancer from Blood Plasma Using a Machine Learning‐Driven Electronic Nose

Advanced Intelligent Systems, EarlyView.
This study introduces a biomarker‐agnostic diagnostic strategy for ovarian cancer, utilizing a machine learning‐enhanced electronic nose to analyze volatile organic compound signatures from blood plasma. By overcoming the dependence on specific biomarkers, this approach enables accurate detection, staging, and cancer type differentiation, offering a ...
Ivan Shtepliuk, Lingyin Meng, Christer Borgfeldt, Jens Eriksson, Donatella Puglisi   +4 more
wiley   +1 more source

Comprehensive review of Bayesian network applications in gastrointestinal cancers. [PDF]

World J Clin Oncol
Zhang MN, Xue MJ, Zhou BZ, Xu J, Sun HK, Wang JH, Wang YY.   +6 more
europepmc   +1 more source

Optisense: Computational Optimization for Strain Sensor Placement in Wearable Motion Tracking Systems

Advanced Intelligent Systems, EarlyView.
A computational framework for optimizing strain sensor placement in wearable motion tracking systems is presented. By combining dense strain mapping with a genetic algorithm, the method discovers counterintuitive yet highly effective configurations that reduce joint angle error by 32%.
Minu Kim, Juhyung Ahn, Jieun Seo, Steve Park, Joo Yong Sim   +4 more
wiley   +1 more source

Comparative Efficacy of Needling and Non-Needling Therapies for Temporomandibular Disorders: A Bayesian Network Meta-Analysis. [PDF]

J Pain Res
Ding X, Liao S, Li T, Qu W, Nie M.
europepmc   +1 more source

Feature Disentangling and Combination Implemented by Spin–Orbit Torque Magnetic Tunnel Junctions

Advanced Intelligent Systems, EarlyView.
Spin–orbit torque magnetic tunnel junctions (SOT‐MTJs) enable efficient feature disentangling and integration in image data. A proposed algorithm leverages SOT‐MTJs as true random number generators to disentangle and recombine features in real time, with experimental validation on emoji and facial datasets.
Xiaohan Li, Yingqian Xu, Caihua Wan, Ran Zhang, Meike Hindenberg, Raik Hoffmann, Shiqiang Liu, Tianyi Zhang, Shilong Xiong, Dehao Kong, Jihao Xia, Fangshuo Gao, Zhuyang Nie, Thomas Kämpfe, Guoqiang Yu, Xiufeng Han   +15 more
wiley   +1 more source

Bayesian network 3D event reconstruction in the Cygno optical TPC for dark matter direct detection. [PDF]

Eur Phys J C Part Fields
Amaro FD, Antonietti R, Baracchini E, Benussi L, Bianco S, Borra F, Capoccia C, Caponero M, Cavoto G, Costa IA, Croce A, Dané E, D'Astolfo M, Dho G, Di Giambattista F, Di Marco E, D'Imperio G, Folcarelli M, Dos Santos JMF, Fiorina D, Iacoangeli F, Islam ZU, Lima HP, Kemp E, Maccarrone G, Mano RDP, Marques DJG, de Carvalho LGM, Mazzitelli G, McLean AG, Meloni P, Messina A, Monteiro CMB, Nobrega RA, Pains IF, Paoletti E, Passamonti L, Petrucci F, Piacentini S, Piccolo D, Pierluigi D, Pinci D, Prajapati A, Renga F, Roque RJC, Roque RJC, Rosatelli F, Russo A, Saviano G, Silva PAOC, Spooner NJC, Tesauro R, Tomassini S, Torelli S, Tozzi D.   +54 more
europepmc   +1 more source

Metalearning‐Driven Inverse Optimization for Precision Microstructure Fabrication in Digital Light Processing Three‐Dimensional Printing

Advanced Intelligent Systems, EarlyView.
Metalearning‐based inverse optimization enables precise microscale three‐dimensional printing using a DLP system. Distorted structures from conventional printing are analyzed via neural network regression, which predicts optimal exposure time and mask design.
Jae Won Choi, Suhyeong Lim, Jeongsu Lee, Cheol Woo Ha   +3 more
wiley   +1 more source