Results 151 to 160 of about 394,931 (262)
Sensitivity of Bayesian Networks to Noise in Their Parameters. [PDF]
Onisko A, Druzdzel MJ.
europepmc +1 more source
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova +4 more
wiley +1 more source
SuperResNET is a powerful integrated software that reconstructs network architecture and molecular distribution of subcellular structures from single molecule localization microscopy datasets. SuperResNET segments the nuclear pore complex and corners, extracts size, shape, and network features of all segmented nuclear pores and uses modularity analysis
Yahongyang Lydia Li +6 more
wiley +1 more source
Natural Gas Purification Plants Based on Interpretive Structural Models and Bayesian Networks. [PDF]
Gong J +5 more
europepmc +1 more source
Predicting Performance of Hall Effect Ion Source Using Machine Learning
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park +8 more
wiley +1 more source
Modeling chronic pain interconnections using Bayesian networks: insights from the Qatar Biobank study. [PDF]
Al-Khinji AAMA, Malouche D.
europepmc +1 more source
A skin‐conformal wearable device based on laser‐induced graphene is developed for continuous strain measurement across the circumference of the forearm for gesture recognition and hand‐tracking applications. Post material optimization, the strain sensor array is integrated with a wearable wireless readout circuit for real‐time control of a robotic arm,
Vinay Kammarchedu +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]
Linghu L +7 more
europepmc +1 more source
Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing
This Roadmap outlines the transformative role of artificial intelligence‐augmented additive manufacturing, highlighting advances in design, monitoring, and product development. By integrating tools such as generative design, computer vision, digital twins, and closed‐loop control, it presents pathways toward smart, scalable, and autonomous additive ...
Ali Zolfagharian +37 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]
Gonzalez BD +10 more
europepmc +1 more source

