In: Cancers, 2021, vol. 13, no. 19, p. 18
Artificial intelligence (AI) uses mathematical algorithms to perform tasks that require human cognitive abilities. AI-based methodologies, e.g., machine learning and deep learning, as well as the recently developed research field of radiomics have noticeable potential to transform medical diagnostics. AI-based techniques applied to medical imaging allow to detect biological abnormalities, to...
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In: Algorithms, 2021, vol. 14, no. 9, p. 25
Recent systems applying Machine Learning (ML) to solve the Traveling Salesman Problem (TSP) exhibit issues when they try to scale up to real case scenarios with several hundred vertices. The use of Candidate Lists (CLs) has been brought up to cope with the issues. A CL is defined as a subset of all the edges linked to a given vertex such that it contains mainly edges that are believed to be...
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(Internal working papers DIUF ; 21-02)
The objective of this document is to provide a non-technical introduction to the field of Artificial Intelligence. It is intended for anyone outside of the data science community curi-ous about the subject, such as researchers from other areas looking for new instruments, legal professionals confronted with automated decision making algorithms or legal tech tools, en-trepreneurs interested in...
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Mémoire de bachelor : Haute école de santé Genève, 2020.
L'imagerie médicale est un domaine en constante évolution et l'intelligence artificielle en fait partie intégrante. Grâce à l'apprentissage profond, cette étude a pour but de démontrer la capacité d'un système de classification à catégoriser des images radiologiques du membre supérieur en fonction des régions anatomiques et incidences d'épaules. En parallèle, nous avons participé...
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In: Environmental and Ecological Statistics, 2015, vol. 22, no. 3, p. 513-534
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(Internal working papers DIUF ; 21-01)
This article is a literature review of Neuralink, brain-machine interfaces (BMIs) and their applications, followed by future possibilities of BMIs and their potential impacts. Currently, BMIs predominantly have therapeutic applications, such as helping people with spinal cord injury by allowing them to control a computer directly with their brain. However, BMIs can also improve learning,...
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In: Empirical Economics, 2020, p. 1-24
This paper examines how anti-corruption educational campaigns affect the attitudes of Russian university students toward corruption and academic integrity in the short run. About 2000 survey participants were randomly assigned to one of four different information materials (brochures or videos) about the negative consequences of corruption or to a control group. While we do not find important...
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Mémoire de bachelor : Haute école de gestion de Genève, 2020 ; TDIBM 83.
Experts in new technologies and economists seem to agree: robotics and deep learning by machines will change most of the economic activities in the coming decades, at a very fast pace. If in the past, technological changes mainly brought about gradual increases of efficiency in human work; robotics and the availability of big data, used with Artificial Intelligence (AI) will bring about...
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Mémoire de bachelor : Haute école de gestion de Genève, 2020 ; TDIG 187.
In this thesis I will analyse different artificial neural network solutions for creating fake portraits. The final objective is to create a photo board with 1 real portrait and 8 fake ones that are indistinguishable from the real world. In order to achieve the final goal, a description of how an artificial neural network works, how to train one is going to be explained. An overview of the...
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In: Journal for General Philosophy of Science, 2014, vol. 45, no. 2, p. 239-262
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