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What is sci.AI

sci.AI is a free platform that “understands” research papers and “explains” them to analytics and search algorithms. It takes biomedical research in plain text and produces semanticized, machine-readable versions.

These structured versions are designed to simplify the publishing process, to provide readers with beautiful easy-to-read html versions of the papers and to help search engines retrieve relevant papers, therefore increasing their impact.

Our vision

The current time-to-market in biomedical innovations is too long. Through the use of relevant algorithms and a global knowledge graph, our goal is to make scientific innovation at least 2x faster.

We believe that timing is vital. The 9.9 millions people diagnosed with dementia in 20151 don’t yet feel better, even when 12.8 k papers mentioning dementia appeared in Pubmed alone2 the same year. A single scientist can’t read them all, extract relevant knowledge and apply it to their own research. This is where text mining algorithms will help.

Our mission

Enabling machines to help us, humans, with scientific research.

Our method

We are creating a common platform to communicate global research results to other researchers and “machine agents” using the same “language”.

sci.AI semanticizes research communication to a single format. Each semanticized text will contribute to the global knowledge graph.

Another major result of our work is the NLP (Natural Language Processing) framework, specialized for biomedical texts processing.

With each milestone, we will deliver products and features that can be used by scientists as authors, scientists as readers, publishers, research centers, text miners, annotators and funding bodies. These will simplify their work, save time and let them focus on discoveries. It will augment scientific research step-by-step thanks to machine intelligence.

History of sci.AI

While working on the predictive analytics system InfinitySciences, we realized that having 30 millions of papers in the database was not enough. Algorithms need prior “explanation” to analyse research reports. Text mining of biomedical texts is therefore a common and challenging task. It is nearly impossible for a single engineer or a small team to create a comprehensive NLP framework. Still, without proper text decomposition and understanding, it is hard to move further in data analysis. So we decided to focus on the NLP part of InfinitySciences and to create the free sci.AI platform.

Is it free?

Yes, semanticization of the papers via the platform, our key service, is free. The idea is simple: if semanticization is free and widely accepted by scientists and publishers, then recipients of research reports will not lose thousands of hours on initial transformation of the plain biomedical texts into a machine-readable format.
We’ll provide custom services on a paid basis to ensure the sustainability of the initiative.

Roadmap

      • 2017 Q1 – Understanding text on a morphological level. Labeling biomedical concepts. Platform for semantic publishing
      • 2017 Q2 – First pilots with publishers
      • 2017 Q4 – Labeling interactions
      • 2018 – Understanding text on semantic level
      • 2019 Q3 – Majority of biomedical papers are enhanced with sci.AI metadata
      • 2020x – Understanding research on context and pragmatics levels. Enabling Literature Based Discoveries

Who we are

As of the beginning of 2017, sci.AI is a start-up team within Xpansa. It is supported by the Xpansa incubator legally and financially. We’ll create a separate entity after the first successful pilots.

Team

Roman Gurinovich – Architect. Bigger challenge – more fun. Co-manager of Xpansa with Oleg Kuryan for the last 9 years.
Alexander Pashuk – Emperor and Full-stack Developer of sci.AI. Loves cool UI and data visualization. He is currently writing his PHD thesis based on sci.AI.
Yuriy Petrovskiy – NLP Data Scientist, practising doctor that transforms ontologies in between appointments.
Elena Moroz – NLP Data Scientist with bioinformatics specialization. Just loves science.
Alexei Scerbacov – Data and Infrastructure Engineer. Can obtain any data, whatever it is. Will join the Tour de France one day.
Alex Dmitrievskiy – NLP Data Scientist, enjoys recurrence in deep learning. Crazy hockey swimmer.
Vasili Puntus – Marketing Manager, the artist behind the amazing sci.AI videos and Twitter followers growth.
Antonia Tiggre – Volunteer Business Developer, has read all books on psychology. Maybe twice.
Oleg Kuryan – technical advisor, co-manager of Xpansa with Roman for the last 9 years. Just married so simply happy.
Yuri Nikolsky – Industry advisor, former Vice President R&D at Thomson Reuters. Literally “feels” what market needs.

The platform is growing and we are currently looking for the advisors; board, team and community members with significant editorial, management, business development and fundraising experience. A Strong belief that semantics and AI will save the world is highly appreciated.

1World Alzheimer Report 2015. Alzheimer’s Disease International (ADI), London http://www.worldalzreport2015.org/
2Dementia mentions in Pubmed

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