Artificial Intelligence‐Based Identification of Common Canine Skin Lesions From Clinical Images
Background: Accurate evaluation of skin lesions is an essential component of dermatological examination, yet it can be time‐consuming and subject to interobserver variability. While artificial intelligence (AI) models have shown reliability in diagnosing specific skin diseases, lesion‐level identification remains underexplored in veterinary dermatology.
Soh‐Yoon Kang +8 more
wiley +1 more source
Protocol for analyzing potential targets of environmental pollutants in human diseases using network toxicology and molecular docking. [PDF]
Hong Y +6 more
europepmc +1 more source
Abstract figure legend A study described in this paper describes a new tool for hiPSC‐CM electromechanical behaviour simulations using mathematical modelling. The model enables in silico assays making drug testing quick, comprehensive and accurate. New hiPSC‐CM models can be used as a platform to integrate in vitro and in silico findings.
Milda Folkmanaite +9 more
wiley +1 more source
Accelerating AOP Development in the AOP-Wiki with AI: A Practical Road Map for the Community. [PDF]
Song Y +4 more
europepmc +1 more source
Abstract figure legend Schematic overview of a flow‐driven in vitro model of the human placental barrier designed to study transport processes during pregnancy. The model recreates key features of the maternal–fetal interface, enabling the investigation of how nutrients and therapeutic compounds cross the placental barrier under physiologically ...
Barbara Fuenzalida +7 more
wiley +1 more source
Exploring the Toxicological Relationship Between Diisononyl Cyclohexane-1,2-dicarboxylate and Atherosclerosis Through Network Toxicology, Machine Learning, and Multi-Dimensional Bioinformatics. [PDF]
Cao J +6 more
europepmc +1 more source
Next generation validation for next generation risk assessment. [PDF]
Kopańska K, Hartung T.
europepmc +1 more source
Potential for Computational Genotoxicity: A Report on Symposium 3 of the 53rd Annual Meeting of the Japanese Environmental Mutagen and Genome Society (JEMS), 2024. [PDF]
Koyama N +4 more
europepmc +1 more source
Environmental toxicant glyphosate induces cardiotoxicity: New insights from network toxicology, integrated machine learning, molecular modeling and multidimensional bioinformatics analysis. [PDF]
Sun M, Wang Y, Tong R, Yan R, Pu J.
europepmc +1 more source

