Visitors   Views   Downloads

Automated data extraction software for medical summary using text mining (T-Library)

View preprint
RT @OpenScienceR: Automated data extraction software for medical summary using text mining (T-Library) https://t.co/LjVg1kSgkP https://t.co…
31 days ago
RT @OpenScienceR: Automated data extraction software for medical summary using text mining (T-Library) https://t.co/LjVg1kSgkP https://t.co…
Automated data extraction software for medical summary using text mining (T-Library) https://t.co/LjVg1kSgkP https://t.co/NXln870Oli
54 days ago
Automated data extraction software for medical summary using text mining (T-Library) https://t.co/Z6Sz00ClTo https://t.co/QcdCFZE0HM
NOT PEER-REVIEWED
"PeerJ Preprints" is a venue for early communication or feedback before peer review. Data may be preliminary.

Additional Information

Competing Interests

The authors declare that they have no competing interests.

Author Contributions

Tomohide Yamada conceived and designed the experiments, authored or reviewed drafts of the paper, approved the final draft.

Yoshinobu Kondo conceived and designed the experiments, authored or reviewed drafts of the paper, approved the final draft.

Ryo Momosaki conceived and designed the experiments, authored or reviewed drafts of the paper, approved the final draft.

Data Deposition

The following information was supplied regarding data availability:

Please contact authors.

Funding

This work is supported by: Japan Foundation for Applied Enzymology, Japan Health Promotion Foundation, Pfizer Health Research Foundation, Manpei Suzuki Diabetes Foundation, The Daiwa Anglo-Japanese Foundation, The TANITA Healthy Weight Community Trust, Daiwa Securities Health Foundation, The Kanae Foundation for the Promotion of Medical Science, Takano foundation, Kishimoto foundation, Foundation for Total Health Promotion, and JDS and EFSD Reciprocal Travel Research Fellowship Programme. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.


Add your feedback

Before adding feedback, consider if it can be asked as a question instead, and if so then use the Question tab. Pointing out typos is fine, but authors are encouraged to accept only substantially helpful feedback.

Some Markdown syntax is allowed: _italic_ **bold** ^superscript^ ~subscript~ %%blockquote%% [link text](link URL)
 
By posting this you agree to PeerJ's commenting policies