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Knowledge Base

Links to resources, books, tutorials and other stuffs that are useful technically.

Read it

Rajkomar, A., Dean, J. and Kohane, I., 2019. Machine learning in medicine. New England Journal of Medicine, 380(14), pp.1347-1358. Paper link
Yoshua Bengio, Yann Lecun, Geoffrey Hinton. Deep Learning for AI Communications of the ACM, July 2021, Vol. 64 No. 7, Pages 58-65. https://cacm.acm.org/magazines/2021/7/253464-deep-learning-for-ai/fulltext

Seminars/Webinars

Our own bi-weekly group seminars: https://github.com/knowlab/bi-weekly-paper-presentation
Usher Institute Events (various seminars): https://www.ed.ac.uk/usher/news-events/events
JAMIA Journal Club: https://www.amia.org/category/webinars/journal-club

Reviews

(Manning et al, 2015) Advances in natural language processing - https://science.sciencemag.org/content/349/6245/261.full
Ghahramani, Z., 2015. Probabilistic machine learning and artificial intelligence. Nature, 521(7553), pp.452-459. https://www.nature.com/articles/nature14541

Natural Language Processing Tutorials

Practical NLP with Spacy, NLTK, and Stanza
- https://realpython.com/natural-language-processing-spacy-python/
- https://spacy.io/usage/spacy-101
- http://www.nltk.org/book/
- https://stanfordnlp.github.io/stanza/biomed.html (Biomedical Models in Stanza)
NLP with machine learning
- https://www.coursera.org/specializations/natural-language-processing
- https://www.youtube.com/playlist?list=PLoROMvodv4rOhcuXMZkNm7j3fVwBBY42z
Curated embedding models
- https://github.com/Separius/awesome-sentence-embedding

Knowledge Graph and NLP

(Michael Galkin) Knowledge Graph in NLP - ACL2020: https://towardsdatascience.com/knowledge-graphs-in-natural-language-processing-acl-2020-ebb1f0a6e0b1

Knowledge Graph

(venturebeat) Why knowledge graphs are key to working with data efficiently, powerfully: https://venturebeat.com/2021/06/28/why-knowledge-graphs-are-key-to-working-with-data-efficiently-powerfully/
(Our own KG book) Exploiting Linked Data and Knowledge Graphs in Large Organisations: https://link.springer.com/book/10.1007%2F978-3-319-45654-6
Ghahramani, Z., 2015. Probabilistic machine learning and artificial intelligence. Nature, 521(7553), pp.452-459. https://www.nature.com/articles/nature14541

Graph Neural Network

Farewell RNNs, Welcome TCNs: https://towardsdatascience.com/farewell-rnns-welcome-tcns-dd76674707c8
A repo with essential readings for GNN: https://github.com/thunlp/GNNPapers

Automated Medical Coding

Lastest papers on automated medical coding from free-text clinical notes: https://github.com/acadTags/medical-coding-NLP

COVID-related

An ongoing curation of COVID-related NLP tools: https://github.com/acadTags/Awesome-COVID-NLP-tools