Results 41 to 50 of about 246,254 (290)

Black-box assisted medical decisions: AI power vs. ethical physician care

open access: yesMedicine, Health care and Philosophy, 2023
I raise an ethical problem with physicians using “black box” medical AI algorithms, arguing that its use would compromise proper patient care. Even if AI results are reliable, my contention is that without being able to explain medical decisions to ...
Berman Chan
semanticscholar   +1 more source

Nonlinear black-box system identification through coevolutionary algorithms and radial basis function artificial neural networks

open access: yesApplied Soft Computing, 2020
The present work deals with the application of coevolutionary algorithms and artificial neural networks to perform input selection and related parameter estimation for nonlinear black-box models in system identification.
H. V. Ayala   +3 more
semanticscholar   +1 more source

Ethical issues of implementing artificial intelligence in medicine

open access: yesDigital Diagnostics, 2023
Artificial intelligence (AI) systems are highly efficient. However, their implementation in medical practice is accompanied by a range of ethical issues. The black box problem is basic to the AI philosophy, although having its own specificity in relation
Maxim I. Konkov
doaj   +1 more source

Black Box Warning: Large Language Models and the Future of Infectious Diseases Consultation

open access: yesClinical Infectious Diseases, 2023
Large language models (LLMs) are artificial intelligence systems trained by deep learning algorithms to process natural language and generate text responses to user prompts.
Ilan S. Schwartz   +3 more
semanticscholar   +1 more source

An Active Learning Methodology for Efficient Estimation of Expensive Noisy Black-Box Functions Using Gaussian Process Regression

open access: yesIEEE Access, 2020
Estimation of black-box functions often requires evaluating an extensive number of expensive noisy points. Learning algorithms can actively compare the similarity between the evaluated and unevaluated points to determine the most informative subsequent ...
Rajitha Meka   +3 more
doaj   +1 more source

Infusing theory into deep learning for interpretable reactivity prediction

open access: yesNature Communications, 2021
Machine learning faces challenges in catalyst design due to its black-box nature. Here, the authors develop a theory-infused neural network approach that integrates deep learning algorithms with the well-established d-band theory of chemisorption for ...
Shih-Han Wang   +4 more
doaj   +1 more source

Black-box optimization methods for hypersonic flow problems [PDF]

open access: yesInternational Journal of Fluid Engineering
This review examines the application of black-box optimization methods to hypersonic flow problems, with a particular emphasis on scenarios where computational fluid dynamics (CFD) simulations function as opaque, nontransparent models.
Davood Hoseinzade   +2 more
doaj   +1 more source

Efficient quantum gates and algorithms in an engineered optical lattice

open access: yesScientific Reports, 2021
In this work, trapped ultracold atoms are proposed as a platform for efficient quantum gate circuits and algorithms. We also develop and evaluate quantum algorithms, including those for the Simon problem and the black-box string-finding problem.
A. H. Homid   +3 more
doaj   +1 more source

Black Box Algorithm Selection by Convolutional Neural Network [PDF]

open access: yes, 2020
9 pages, 4 figures, 5 tables, journal ...
Yaodong He, Shiu Yin Yuen
openaire   +2 more sources

The comparison of different PDP-type self-adaptive schemes for the cooperation of GA, DE, and PSO algorithms [PDF]

open access: yesITM Web of Conferences
Many global optimization problems are presented as a black-box model, in which there is no information on the objective function properties. Traditional optimization algorithms usually can't effectively solve that kind of problems.
Sopov Anton, Karaseva Tatiana
doaj   +1 more source

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