Medical_AI Paper Getter
Web scraping system for extracting medical-like AI conference papers.
Available Conferences
Machine Learning & Artificial Intelligence
IJCAI, NIPS, ICML, ICLR, IJCNN
Computer Vision
CVPR, ICCV
Natural Language Processing
ACL, NAACL, EMNLP, CoNLL, COLING, IJCNLP, EACL, LREC, CL, SEMEVAL, TACL, ALTA, HLT, JEP-TALN-RECITAL, MUC, PACLIC, RANLP, ROCLING-IJCLCLP, TINLAP, TIPSTER
Usage(1): In Python3 Code
Overview
Import module:
import medical.aiTo get medical-like AI papers in CVPR 2017 & 2018, create a Query instance and use .search() method:
query = medical.ai.Query(conference='cvpr', year=[2017, 2018])
result = query.search()>>> Connecting for CVPR 2017 ...
>>> Connecting for CVPR 2018 ...
>>> Download from CVPR 2017 ... 784 papers Complete!
>>> Download from CVPR 2018 ... 980 papers Complete!
Get information of medical-like AI papers:
for conference in result:
print(conference.conference_name)
print(conference.year)
for paper in conference.medical_ai_papers:
print(paper.title)
print(paper.url)
print(paper.author) # list ['author1', 'author2', ... ]
print(paper.abstract)Get information of medical-like & non-medical-like AI papers:
for conference in result:
print(conference.conference_name)
print(conference.year)
for paper in conference.papers:
print(paper.title)
print(paper.url)
print(paper.author) # list ['author1', 'author2', ... ]
print(paper.abstract)
print(paper.medical) # True or FalseQuiet Mode
If you want standard output to be more quiet, use config as this:
import medical.ai
myconfig = medical.ai.Config(quiet=True)
query = medical.ai.Query(conference='cvpr', year=[2017, 2018])
result = query.search(config=myconfig)Usage(2): via command-line
Overview
Run medical/ai.py on the shell:
python3 medical/ai.py <CONFERENCE> <YEAR>
e.g. For 'cvpr 2017', you get 8 medical-like conference papers:
python3 medical/ai.py cvpr 2017
Connecting for CVPR 2017 ...
Downloading from CVPR 2017 ... 784 papers Complete!
===================================
CVPR 2017
Direct Photometric Alignment by Mesh Deformation.
https://doi.org/10.1109/CVPR.2017.289
ChestX-Ray8: Hospital-Scale Chest X-Ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases.
https://doi.org/10.1109/CVPR.2017.369
MDNet: A Semantically and Visually Interpretable Medical Image Diagnosis Network.
https://doi.org/10.1109/CVPR.2017.378
Joint Sequence Learning and Cross-Modality Convolution for 3D Biomedical Segmentation.
https://doi.org/10.1109/CVPR.2017.398
Fine-Tuning Convolutional Neural Networks for Biomedical Image Analysis: Actively and Incrementally.
https://doi.org/10.1109/CVPR.2017.506
Simultaneous Super-Resolution and Cross-Modality Synthesis of 3D Medical Images Using Weakly-Supervised Joint Convolutional Sparse Coding.
https://doi.org/10.1109/CVPR.2017.613
Multiple-Scattering Microphysics Tomography.
https://doi.org/10.1109/CVPR.2017.614
Expert Gate: Lifelong Learning with a Network of Experts.
https://doi.org/10.1109/CVPR.2017.753
===================================
Medical-like AI papers in CVPR 2017: 8 / 784
Use -m or -markdown option to display result as markdown links:
python3 medical/ai.py cvpr 2017 -m
Connecting for CVPR 2017 ...
Downloading from CVPR 2017 ... 784 papers Complete!
===================================
CVPR 2017
[Direct Photometric Alignment by Mesh Deformation.](https://doi.org/10.1109/CVPR.2017.289)
[ChestX-Ray8: Hospital-Scale Chest X-Ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases.](https://doi.org/10.1109/CVPR.2017.369)
...
[Expert Gate: Lifelong Learning with a Network of Experts.](https://doi.org/10.1109/CVPR.2017.753)
===================================
Medical-like AI papers in CVPR 2017: 8 / 784
Use --copy option to copy result onto clipboard:
python3 medical/ai.py cvpr 2017 -m --copy
Connecting for CVPR 2017 ...
Downloading from CVPR 2017 ... 784 papers Complete!
===================================
CVPR 2017
[Direct Photometric Alignment by Mesh Deformation.](https://doi.org/10.1109/CVPR.2017.289)
[ChestX-Ray8: Hospital-Scale Chest X-Ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases.](https://doi.org/10.1109/CVPR.2017.369)
[MDNet: A Semantically and Visually Interpretable Medical Image Diagnosis Network.](https://doi.org/10.1109/CVPR.2017.378)
...
[Expert Gate: Lifelong Learning with a Network of Experts.](https://doi.org/10.1109/CVPR.2017.753)
===================================
Medical-like AI papers in CVPR 2017: 8 / 784
* * * Copied this result to clipboard * * *
To browse all available options, input python3 medical/ai.py -h or python3 medical/ai.py --help:
usage: medical/ai.py [-h] [-q] [--copy] [-m | --html]
[--title-only | --url-only]
conference year
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Pickup medical AI paper titles and URLs from specified conference and year.
会議名と年数を指定すると, 医療に関連するAI論文のみを探し出してタイトルとURLを列挙します.
To get from ACL 2019, input like this: python3 medical/ai.py acl 2019
例えばACL 2019採択論文から探すには本プログラムを python3 medical medical/ai.py acl 2019 と実行してください.
Conference name is case insensitive.
会議名は大文字でも小文字でも構いません.
To output HTML link tags or markdown links, use options below.
以下に示すオプションを使うと, 結果をHTMLリンクタグやMarkdownリンクとして出力することも可能です.
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positional arguments:
conferences_and_years
speficy conferences and years
example1: acl 2019
example2: acl naacl 2019
example3: acl 2018 2019
example4: acl naacl 2018 2019
optional arguments:
-h, --help show this help message and exit
-q, --quiet be more quiet
--copy copy result to clipboard
-a, --all get also non-medical AI papers
-m, --md, --markdown output as markdown links
collaborates with --url-only
ignores --title-only
--html output as HTML <a> tags
collaborates with --url-only
ignores --title-only
--title-only output paper title only
--url-only output paper URL only