Results 201 to 210 of about 113,736 (262)
Artificial intelligence is redefining network pharmacology (NP). By integrating knowledge graph engineering, geometric deep learning, multiomics anchoring, and generative reasoning, AI‐driven NP (AI‐NP) transforms static target mapping into dynamic, predictive modeling.
Cong Wang +9 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]
Carrodano C.
europepmc +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
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
Sensitivity analysis of unsafe behaviors in the spinning and weaving factories: Exploring the association with burnout and resilience using Bayesian networks. [PDF]
Azimi R +5 more
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
CausNet-partial: 'Partial Generational Orderings' based search for optimal sparse Bayesian networks via dynamic programming with parent set constraints. [PDF]
Sharma N, Millstein J.
europepmc +1 more source
This paper presents a lidar‐based sensor node design and a rule‐based state observer for edge‐based traffic participant tracking. Unlike other state‐of‐the‐art methods, this state observer enables real‐time, CPU‐only edge processing without relying on machine learning approaches.
Simon Schäfer +2 more
wiley +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]
Wang M +9 more
europepmc +1 more source

