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Data in Brief, 2022 With this article, we present a repository containing datasets, analysis code, and some outputs related to a paper in press at Cognition. The data were collected as part of a pre-test, pilot test, and main study all designed in SurveyGizmo and ...
Molly S. Quinn +2 more
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Identification of Tumor-Specific MRI Biomarkers Using Machine Learning (ML)
Diagnostics, 2021 The identification of reliable and non-invasive oncology biomarkers remains a main priority in healthcare. There are only a few biomarkers that have been approved as diagnostic for cancer.
Rima Hajjo +3 more
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ACL2(ml): Machine-Learning for ACL2 [PDF]
Electronic Proceedings in Theoretical Computer Science, 2014 ACL2(ml) is an extension for the Emacs interface of ACL2. This tool uses machine-learning to help the ACL2 user during the proof-development. Namely, ACL2(ml) gives hints to the user in the form of families of similar theorems, and generates auxiliary ...
Jónathan Heras +1 more
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Causal ML: Python package for causal inference machine learning
SoftwareX, 2023 “Causality” is a complex concept that is based on roots in almost all subject areas and aims to answer the “why” question. Causal inference is one of the important branches of causal analysis, which assumes the existence of relationships between ...
Yang Zhao, Qing Liu
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Machine Learning (ML) in Medicine: Review, Applications, and Challenges
Mathematics, 2021 Today, artificial intelligence (AI) and machine learning (ML) have dramatically advanced in various industries, especially medicine. AI describes computational programs that mimic and simulate human intelligence, for example, a person’s behavior in ...
Amir Masoud Rahmani +6 more
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Optimisation of Knowledge Management (KM) with Machine Learning (ML) Enabled
Information, 2023 The emergence of artificial intelligence (AI) and its derivative technologies, such as machine learning (ML) and deep learning (DL), heralds a new era of knowledge management (KM) presentation and discovery. KM necessitates ML for improved organisational
Muhammad Anshari +4 more
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ML-AdVInfect: A Machine-Learning Based Adenoviral Infection Predictor
Frontiers in Molecular Biosciences, 2021 Adenoviruses (AdVs) constitute a diverse family with many pathogenic types that infect a broad range of hosts. Understanding the pathogenesis of adenoviral infections is not only clinically relevant but also important to elucidate the potential use of ...
Onur Can Karabulut +5 more
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ML meets MLn: Machine learning in ligand promoted homogeneous catalysis
Artificial Intelligence Chemistry, 2023 The benefits of using machine learning approaches in the design, optimisation and understanding of homogeneous catalytic processes are being increasingly realised.
Jonathan D. Hirst +7 more
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Journal on Interactive Systems, 2022 The way Complex Machine Learning (ML) models generate their results is not fully understood, including by very knowledgeable users. If users cannot interpret or trust the predictions generated by the model, they will not use them.
Bárbara Gabrielle C. O. Lopes +3 more
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Stock Market Prediction Using Machine Learning(ML)Algorithms
Advances in Distributed Computing and Artificial Intelligence Journal, 2020 Stocks are possibly the most popular financial instrument invented for building wealth and are the centerpiece of any investment portfolio. The advances in trading technology has opened up the markets so that nowadays nearly anybody can own stocks.
Muhammad UMER +2 more
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