Artificial intelligence in cardiology: the debate continues

In 1955 when John McCarthy and his colleagues proposed their first study of artificial intelligence, they suggested that “every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it”. Whether that might ever be possible would depend on how we define intelligence, but what is indisputable is that new methods are needed to analyse and interpret the copious information provided by digital medical images, genomic databases, and biobanks. Technological advances have enabled applications of artificial intelligence (AI) including machine learning (ML) to be implemented into clinical practice, and their related scientific literature is exploding. Advocates argue enthusiastically that AI will transform many aspects of clinical cardiovascular medicine, while sceptics stress the importance of caution and the need for more evidence. This report summarises the main opposing arguments that were presented in a debate at the 2021 Congress of the European Society of Cardiology. AI is an advanced analytical technique that should be considered when conventional statistical methods are insufficient, but testing a hypothesis or solving a clinical problem—not finding another application for AI—remains the most important objective. AI and ML methods should be transparent and interpretable, if they are to be approved by regulators and trusted to provide support for clinical decisions. Physicians need to understand AI methods and collaborate with engineers. Few applications have yet been shown to have a positive impact on clinical outcomes, so investment in research is essential.

ARTIFICIAL INTELLIGENCE AND COMPUTER VISION – A MATCH MADE IN HEAVEN?

After becoming independent in 1957, Malaysia continued as an agricultural country but quickly grew into a manufacturing nation in a relatively short time. Literally from nowhere, the manufacturing sector now commands more than 38% of the nation’s GDP overtaking the agriculture sector which commands just slightly above 7%. In addition to the multinational manufacturers who are mainly in the electrical and electronics sectors, there are also other smaller producers who produce for the rest of the world. Nevertheless in order to compete, they cannot just rely on manual labour whether local or foreign, to produce high volume and high quality goods at a competitive price. With intense competition, even the old way of making many products to satisfy the global appetite for good products from both the brick-and-mortar shops to your huge online shops is no longer adequate. Manual operations in the manufacturing process can come in various forms, ranging from the very simple but monotonous and repetitive to the highly complex or sophisticated. In the quality department many of the local manufacturers have chosen to use human labour to ensure their quality is maintained. For many of these highly repetitive but relatively simple tasks, the human operators need to be properly trained for an appropriate length of time before they can perform effectively. Other than the intelligence of these operators, their ability to detect deviations from the desired patterns are also utilised. And this is where artificial intelligence and computer vision can help. The term artificial intelligence was first coined at the Dartmouth Summer Research Project on Artificial Intelligence by John McCarthy in 1956. While there are many definitions, Ray Kurzweil, an American inventor and futurist defines it as machines that perform functions that require intelligence when performed by humans[1]. On the other hand, computer vision deals with how computers can gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to understand and automate tasks that the human visual system can do. This paper shows how artificial intelligence combined with computer vision can be used to improve productivity and effectiveness in three different areas.

Artificial Intelligence in the Pharmacy Profession

The scientist named ‘John McCarthy' used the term "Artificial Intelligence" for the very first time in 1956. Previously, it is only limited to engineering field, but in the recent years, it is briefly introduced into the other fields like pharma, healthcare, business, public sector etc. This review article presented to help as a short presentation of AI for the doctors and pharmacists. Here we describe the AI in various field of medical care, its advantage as well as disadvantages in pharmacy, and its tools. It is greatly advanced into the decision-making, problem solving and critical thinking and having applications in various fields like business, pharmacy, health care, and engineering as well. Now the robots are using in the various medical procedures as they are more trustworthy for doctors, as they are more advanced in their work, as they can do any task within the short time period and effectively than humans. This is concluded that AI is the new evolving field in every sector, even in pharmacy, and it need more development for updating the current scenario as well as for new researches.

The Technical Buzzword: Artificial Intelligence

AI is the incredibly exciting technique to the world. According to John McCarthy it is “The science and engineering of making intelligent machine, especially intelligent computers”. AI is the way of creating extraordinary powerful machine which is similar as human being. The AI is being accomplished by studying how human brain think, how they learn, decide, work, solving the real world problem and after that verify the outcomes and studying it. Primarily you can learn here what AI is and how it works, its types, its history, its agents, its applications, its advantages and disadvantages.

The Technical Buzzword: Artificial Intelligence

AI is the incredibly exciting technique to the world. According to John McCarthy it is “The science and engineering of making intelligent machine, especially intelligent computers”. AI is the way of creating extraordinary powerful machine which is similar as human being. The AI is being accomplished by studying how human brain think, how they learn, decide, work, solving the real world problem and after that verify the outcomes and studying it. Primarily you can learn here what AI is and how it works, its types, its history, its agents, its applications, its advantages and disadvantages.

Is AI in Your Future?

AI was first coined by John McCarthy in 1956. Vannevar Bush penned an article, “As We Make Think,” that was first published in The Atlantic, and five years later, Alan Turning wrote a paper on the notion of machines being able to simulate human beings. AI had a number of significant contributors, which this chapter chronicles along with the definitions and their achievements. This chapter will provide an introduction, history, and overview of AI. It will also provide examples of the four waves of AI and the current applications and future applications of AI.

Big data e inteligencia artificial: directrices para no perderse en un laberinto sin fin

La expresión “inteligencia artificial” (IA), usada por vez primera por John McCarthy en 1955, describe un amplio, creciente y confuso terreno de investigaciones y de aplicaciones, con usos amplios y restringidos, enfoques diversos y a veces contrapuestos. La expresión, además, debe situarse en un contexto más amplio para aprehenderla cabal y totalmente: la evolución constante, con progresión geométrica, de las tecnologías de la información y la comunicación (TIC), queha dado lugar a lo que se suele denominar cuarta revolución industrial. Esta cuarta revolución, a diferencia de las anteriores, afecta a la naturaleza, fundamento y funcionamiento de la totalidad de la vida social de la especie humana; es decir, afecta a las dimensiones tecnológicas, económicas, políticas y culturales de todas nuestras sociedades. Por ello a menudo se dice que esta cuarta revolución tiene un impacto sistémico, y por ende disruptivo (altera) y también reestructurador (modifica sinergias y elementos fundantes y articuladores) del sistema social, al afectar a estratos superficiales, intermedios y profundos de nuestra organización social.

Artificial Satisfaction - The Brother of Artificial Intelligence

John McCarthy (September 4, 1927 – October 24,2011) was an American computer scientist and cognitive scientist. The term “Artificial Intelligence” was coined by him(Wikipedia, 2020). Satish Gajawada (March 12, 1988 – Present) is an Indian Independent Inventor and Scientist. He coined the term “Artificial Satisfaction” in this article (Gajawada, S., and Hassan Mustafa, 2019a). A new field titled “Artificial Satisfaction” is introduced in this article. “Artificial Satisfaction” will be referred to as “The Brother of Artificial Intelligence” after the publication of this article. A new algorithm titled “Artificial Satisfaction Algorithm (ASA)” is designed and implemented in this work. For the sake of simplicity, Particle Swarm Optimization (PSO) Algorithm is modified with Artificial Satisfaction Concepts to create the“Artificial Satisfaction Algorithm (ASA).” PSO and AS Aalgorithms are applied on five benchmark functions. A comparision is made between the results obtained. The focus of this paper is more on defining and introducing “Artificial Satisfaction Field” to the rest of the world rather than on implementing complex algorithms from scratch.