This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani +7 more
wiley +1 more source
Optimization strategies for elderly hearing aid user satisfaction based on the Kano QFD integrated model and FAD theory. [PDF]
Ren Y, Cha K.
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From Principles to Practice: Engineering Responsible AI for Geospatial Intelligence. [PDF]
Hassan M +4 more
europepmc +1 more source
Multi-domain identification of myocardial infarction incidence using explainable AI: the overlooked role of periodontal health. [PDF]
Hussein M +5 more
europepmc +1 more source
Identification of genetic variants associated with lupus nephritis in a Taiwanese cohort through systematic genetic screening. [PDF]
Lee JC +9 more
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Evaluation of tip fold over in 1,575 cochlear implant electrode arrays. [PDF]
Magradze G +7 more
europepmc +1 more source
Genomic loci associated with Fusarium stalk rot resistance and related agronomic traits in maize. [PDF]
Asiedu DD +5 more
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A Simple Understanding of Quantum Electrodynamics Using Bohmian Trajectories: Detecting Non-Ontic Photons. [PDF]
Seoane JJ, Benali A, Oriols X.
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Machine learning analysis of population-wide plasma proteins identifies hormonal biomarkers of Parkinson's disease. [PDF]
Chaudhry F, Kim TW, Elemento O, Betel D.
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Genetic parameters for welfare, infestation level, and inflammatory response traits in cage-free laying hens experimentally infested with northern fowl mites (Ornithonyssus sylviarum). [PDF]
Sculley ER +7 more
europepmc +1 more source

