Artificial Intelligence (AI) in cloud integrated, open access pathology publications: perspectives on 2020.
Goal: To describe, maintain and further develop the communication network of medical sciences www.diagnosticpathology.eu that publishes electronically submitted peer reviewed medical articles and fully takes advantage of its electronic environment, and to give the reader the opportunity to view digitized whole slide images (virtual slides, VS), to measure image objects, and to annotate images and text.
Background: The unique open access, peer reviewed journal www.diagnosticpathology.eu is embedded in a communication environment of different cloud components. The components include several distributed servers and databank systems such as access to article integrated VS, data storage, or scientific data banks (atlas of fine granulate and natural and synthetic fiber hazards).
Implementation specificities: Theoretical considerations on specific substantial differences between the physical real world and its virtual transformations guide the implementation. The differences include, for example, the minimum number of mandatory space dimensions, of their essential (ir)-reversibility of objects, structures, and functions as well as the relationship of image features to the observation time.
The implemented system focuses on communication issues in tissue – based science only. Its volunteers allow disregard any predominantly financial impact such as financial profit. Artificial intelligence (AI) is used to maintain its sustainability, connectivity, distribution, measurement and discussion of medical images, especially microscopic slides.
2019 Data: The journal and its concurrent operation of interactive communication demonstrate the advantage of AI in open access publication. VS are ready to be screened and annotated by any reader worldwide. QR codes provide DOI registration and upload of oral presentations by the auditorium. Interactive publication permits the release of a distinct continuous article chain. Annotations of VS images can be transferred in public or private databanks. The reader is invited to check his impression of marker scores by own automated measurements.
Perspectives: Applications of AI in tissue – based diagnosis, communication and implementation are not limited to deep learning, quality assurance or so-called diagnosis assistants. AI is on the way to significantly modify medical diagnostics and treatment. These modifications will, in addition, modify our understanding of disease and life. www.diagnosticpathology.eu is one of the pathfinders and pioneers in this unavoidable process.
Keywords: Artificial Intelligence, Open Access Journal, Virtual Slide, Deep Learning, Tissue – based Diagnosis.
The exemplarily included virtual slides and AVI Videos are published in http://dx.doi.org/10.17629/www.diagnosticpathology.eu-2018-4:269
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