The difficulty in digesting the related growing scientific information, not conclusive scientific evidence of some experimental studies, and the influence of social media platforms have caused that gluten-related information could be misunderstood or misused in the last years
The objective was to establish a corpus to identify and analyze the relevant health-related relationships supported in the literature
A semi-automatic workflow based on a deep learning model support the automatic identification of hidden biochemical relationTypes in the scientific publications
The literature extracted interactions are combined with the social media discussion to show a novel knowledge space
The number of exploratory research studies testing the elimination of some alimentary proteins in specific diets to treat patients with (or without) an apparent nutritional association has highly increased in recent years.
Different social factors promote a self-prescribed GFD, including active consumer-directed marketing by manufacturers and retail outlets, conventional media coverage, internet information, social media networks, and claims in the mainstream press of the therapeutic benefits of gluten avoidance. For example, nearly 50% of 910 athletes (including world-class and Olympic medallists) adhere to GFD because they perceive it as more healthy and providing energy benefits [REF]
Therefore, with the increased use of the Internet, online information is widely used by the general population to collect knowledge and learning about health and alimentary-related topics. In 2016 a research questionnaire-derived data indicated that individuals prefer as sources of health-related information Internet, print media sources, cookbooks, disease support groups, and other patient's experiences over medical books and even the family doctor
Social media platforms play an essential role in proper medical education of society and signalling potential risks in alimentary fads. This study denoted the importance that the gluten-related information has in the different communities, the problem associated to the missinformation and desinformation, and important the role that health organisations and stakeholders had in supporting truthful information and countering misinformation
A expert human and a training AI collaborate to curate and structured the gluten related scientific knowledge.The database system contains:
5800
Were the total documents manually annotated taking into account their health-related implications
8
Were the total different annotations identified categories such as: Disease, Symptoms, Compunds, Genes...
9000
were the total relevant health-related interactions manually identified and supported by the scientific literature
130561
Were the public messages processed to identify social main topics discussed on the social networks
Find curated relations between different biochemical compounds based on the literature in a simple and pretty way
Use complex filters to find hidden paths between biochemical compounds, disease, symptoms and improve or speed up your biomedical research .
You also could find bibliometrics analysis of yor searches. Information as most relevant authors for a related disease, compound or symptom, most relevant funding agencies and more information are waiting
In this platform you are be able to preview the annotated abstracts of the gluten-related literature where the extracted biochemical relations visualised
Our mission is the application of Artificial Intelligence (AI) and Text Mining (TM) techniques together with Information and Communications Technologies (ICT) to solve problems in biomedicine and computer science. Following there are the team that participate in the development of this project
The documents are obtained through pubmed's public API, through which we download the abstracts that are annotated.
No, not all documents have been manually annotated. you will be able to see clearly and concisely which information comes from an AI and which comes directly from the manual curation of a human.
Search relations related to one biochemical compound
Search relations related to a specific family or node category
Search relations related to a specific year
Search relations related to a specific biochemical relation type
Search relations related to a specific article publication type
Search relations related to two biochemical compounds
In terms of health information, research questionnaire-derived data indicate that individuals prefer as sources of health-related information Internet, print media sources, cookbooks, disease support groups, and other patient's experiences over medical books and even the family doctor [ref]. For this reason it is more and more necessary the appearance of sites like these that allow experts and general people to find in a simple way information contrasted by the scientific literature about diseases whose amount of misinformation and economic interests are growing everyday.
This work has these related publications that you can cite to help to support our work:
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