scholarly journals Artificial Intelligence Applications in Nutrition and Dietetics

Author(s):  
Izzet Ulker ◽  
Feride Ayyildiz

Artificial intelligence (AI) is a branch of computer science whose purpose is to imitate thought processes, learning abilities, and knowledge management. The increasing number of applications in experimental and clinical medicine is striking. An artificial intelligence application in the field of nutrition and dietetics is a fairly new and important field. Different apps related to nutrition are offered to the use of individuals. The importance of individual nutrition has also triggered the increase in artificial intelligence apps. It is thought that different apps such as food preferences and dietary intake can play an important role in health promotion. Researchers may have some difficulties such as remembering the frequency or amount of intake in assessment of dietary intake. Some applications used in the assessment of food consumption contribute to overcoming these difficulties. Besides, these apps facilitate the work of researchers and provide more reliable results than traditional methods. The apps to be used in the field of nutrition and dietetics should be developed by considering the disadvantages. It is thought that artificial intelligence applications will contribute to both the improvement of health and the assessment and monitoring of nutritional status.

Nutrients ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 322
Author(s):  
Jarosław Sak ◽  
Magdalena Suchodolska

Artificial intelligence (AI) as a branch of computer science, the purpose of which is to imitate thought processes, learning abilities and knowledge management, finds more and more applications in experimental and clinical medicine. In recent decades, there has been an expansion of AI applications in biomedical sciences. The possibilities of artificial intelligence in the field of medical diagnostics, risk prediction and support of therapeutic techniques are growing rapidly. The aim of the article is to analyze the current use of AI in nutrients science research. The literature review was conducted in PubMed. A total of 399 records published between 1987 and 2020 were obtained, of which, after analyzing the titles and abstracts, 261 were rejected. In the next stages, the remaining records were analyzed using the full-text versions and, finally, 55 papers were selected. These papers were divided into three areas: AI in biomedical nutrients research (20 studies), AI in clinical nutrients research (22 studies) and AI in nutritional epidemiology (13 studies). It was found that the artificial neural network (ANN) methodology was dominant in the group of research on food composition study and production of nutrients. However, machine learning (ML) algorithms were widely used in studies on the influence of nutrients on the functioning of the human body in health and disease and in studies on the gut microbiota. Deep learning (DL) algorithms prevailed in a group of research works on clinical nutrients intake. The development of dietary systems using AI technology may lead to the creation of a global network that will be able to both actively support and monitor the personalized supply of nutrients.


2020 ◽  
Author(s):  
Ying Liu ◽  
Ziyan Yu ◽  
Shuolan Jing ◽  
Honghu Jiang ◽  
Chunxia Wang

BACKGROUND Artificial intelligence (AI) has penetrated into almost every aspect of our lives and is rapidly changing our way of life. Recently, the new generation of AI taking machine learning and particularly deep convolutional neural network theories as the core technology, has stronger learning ability and independent learning evolution ability, combined with a large amount of learning data, breaks through the bottleneck limit of model accuracy, and makes the model efficient use. OBJECTIVE To identify the 100 most cited papers in artificial intelligence in medical imaging, we performed a comprehensive bibliometric analysis basing on the literature search on Web of Science Core Collection (WoSCC). METHODS The 100 top-cited articles published in “AI, Medical imaging” journals were identified using the Science Citation Index Database. The articles were further reviewed, and basic information was collected, including the number of citations, journals, authors, publication year, and field of study. RESULTS The highly cited articles in AI were cited between 72 and 1,554 times. The majority of them were published in three major journals: IEEE Transactions on Medical Imaging, Medical Image Analysis and Medical Physics. The publication year ranged from 2002 to 2019, with 66% published in a three-year period (2016 to 2018). Publications from the United States (56%) were the most heavily cited, followed by those from China (15%) and Netherlands (10%). Radboud University Nijmegen from Netherlands, Harvard Medical School in USA, and The Chinese University of Hong Kong in China produced the highest number of publications (n=6). Computer science (42%), clinical medicine (35%), and engineering (8%) were the most common fields of study. CONCLUSIONS Citation analysis in the field of artificial intelligence in medical imaging reveals interesting information about the topics and trends negotiated by researchers and elucidates which characteristics are required for a paper to attain a “classic” status. Clinical science articles published in highimpact specialized journals are most likely to be cited in the field of artificial intelligence in medical imaging.


Author(s):  
Almina Seckanovic ◽  
Marijana Sehovac ◽  
Lemana Spahic ◽  
Irma Ramic ◽  
Nuraiym Mamatnazarova ◽  
...  

2014 ◽  
Vol 898 ◽  
pp. 763-766
Author(s):  
Zhi Hao Li

The research and application of artificial intelligence has a very wide range in intelligent robot field. Intelligent robot can not only make use of artificial intelligence gain access to external data, information, (such as stereo vision system, face recognition and tracking, etc.), and then deal with it so as to exactly describe external environment, and complete a task independently, owing the ability of learning knowledge, but also have self-many kinds of artificial intelligence like judgment and decision making, processing capacity and so on. It can make corresponding decision according to environmental changes. Its application range is expanding. In deep sea exploration, star exploration, mineral exploration, heavy pollution, domestic service, entertainment clubs, health care and so on, the figure of intelligent robots artificial intelligence application can all be seen.


2021 ◽  
Vol 2021 (6) ◽  
pp. 214-234
Author(s):  
Irina Kosorukova ◽  
◽  
Anastasia Ligai ◽  
Vadim Mejinski ◽  
◽  
...  

Sign in / Sign up

Export Citation Format

Share Document