artificial intelligence machine learning 2019


Machine Learning is the learning in which machine can learn by its own without being explicitly programmed.
It is an application of AI that provide system the ability to automatically learn and improve from experience.

New ethical challenges of digital technologies, machine learning and artificial intelligence in public health: a call for papers
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Digital technologies and their applications to public health1 are expanding quickly. The World Organizations (WHOs) Member States are increasingly adopting the use of digital technologies in the health sector, exploring the use of data for decision-making and consider- ing new solutions

Artificial intelligence and machine learning : What managers need to know
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In 200 Ken Jennings set a record for the largest total winnings and longest undefeated streak on the television game show Jeopardy ($2.5 million and 74 days, respectively). In 201 IBM invited Jeopardy to present the show from its artificial intelligence (AI) base in

Primed for Psychiatry: The role of artificial intelligence and machine learning in the optimization of depression treatment.
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Depression is a leading source of medical disability and is experienced by over 322 million people worldwide. Despite its increasingly significant burden and a pressing need for effective treatment, depression has been persistently difficult to treat. Current common The benefits of machine learning (ML) and artificial intelligence (AI) lie in controlling limits of production such as handling complexity, generating value out of big data as well as gaining efficiency. However, the application is not a straightforward endeavour. Every company has

7 Artificial Intelligence and Machine Learning as a Predictive Tool for Acute Kidney Injury in Trauma and Severely Burned Patients
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Introduction Kidney injury doubles burn mortality thus, early prediction of acute kidney injury (AKI) in the burn population could benefit from artificial intelligence (AI) and machine learning (ML). Our objective in this study was to build and assess the theoretical

Recent Advancements in Machine Learning and Artificial Intelligence Techniques for Cancer Diagnosis
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In the current epoch of information age, the medical field is being upgraded at an alarming rate especially in the field of cancer diagnosis and rightly so as cancer research is one of the most complex and mindbending challenges. The effects of cancer can only be subdued if it

Machine Learning and Artificial Intelligence
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Machine Learning and Artificial Intelligence in Higher Education: A State-of-the-Art Report on the German University Landscape
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This report provides an overview of some promising applications of artificial intelligence (AI) in German universities. Although the AI sector is booming, the higher education sector seems to have benefited little from this boom thus far. In any case, schools and universities

Utility of Artificial Intelligence and Machine Learning in Cybersecurity
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This work was performed in support of the Army Software Marketplace Acquisition Strategy project (DI-5-4630). The Army has identified the need to reduce costs and delivery time across the enterprise related to software generation, access, management, and sustainment

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications
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The papers in this volume were part of the technical conference cited on the cover and title page. Papers were selected and subject to review by the editors and conference program committee. Some conference presentations not be available for publication. Additional

Are Tokenization, Moving Target Protection Technology, Biometric Authentication, Machine Learning , Artificial Intelligence , and Quantum Cryptography the
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Iansiti and Richards,(2006), indicated that a number of networks of industries organized to deliver services to the end users. This network of industries is termed business echosystems. The amount of dissimilar technologies oriented to facilitate common daily

The Economics of Applications of Artificial Intelligence and Machine Learning in Agriculture
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The global population is expected to reach more than nine billion by 2050, requiring a growing in agricultural production by 70% in order to suit the demand. Only about 10% of this growth come from availability of unused lands, with the result that the rest of 90

Artificial Intelligence Driven Resiliency with Machine Learning and Deep Learning Components
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The future of any business from banking, e-commerce, real estate, homeland security, healthcare, marketing, the stock market, manufacturing, education, retail to government organizations depends on the data and analytics capabilities that are built and scaled. The

The Future of Artificial Intelligence (AI) and Machine Learning (ML) in Landscape Design: A Case Study in Coastal Virginia, USA
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There have been theory-based endeavours that directly engage with AI and ML in the landscape discipline. By presenting a case that uses machine learning techniques to predict variables in a coastal environment, this paper provides empirical evidence of the

Literature Reviews on Applying Artificial Intelligence / Machine Learning to Software Engineering Research Problems: Preliminary
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This paper is aimed to explore the application of Artificial Intelligence / Machine Learning (AI/ML) to software engineering research problems. Which activities of software engineering use AI/ML the most for solving research problems The scope of the paper is to preliminary

Introduction to the Minitrack on Promises and Perils of Artificial Intelligence and Machine Learning : Disruption, Adoption, Dehumanisation, Governance, Risk and
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Given that AI and ML tools are becoming a part of our everyday lives, it is critical that researchers and practitioners understand their state of art, adoption and influence. Improperly deployed AI and ML tools can violate privacy, threaten safety, and take

Contribution of artificial intelligence and machine learning to the assessment of the safety of critical software used in railway transport
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Contribution of artificial intelligence and machine learning to the

Deconstructing the Final Frontier of Artificial Intelligence : Five Theses for a Constructivist Machine Learning .
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Ambiguity and diversity in human cognition can be regarded a final frontier in developing equivalent systems of artificial intelligence . Despite astonishing accomplishments, modern machine learning algorithms are still hardly more than adaptive systems. Deep neural

Artificial General Intelligence , Machine Learning and Language
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Since the very first programmable computers, the idea of making electronic brains computer intelligences has inspired countless computer scientist to work towards the goal true computer intelligence . With this goal came the field of Artificial Intelligence and in 1956 the

Introduction to Artificial Intelligence and Machine Learning
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