Skip to content

Commit b208192

Browse files
committed
add links to readme
1 parent 52fa4f5 commit b208192

File tree

1 file changed

+6
-0
lines changed

1 file changed

+6
-0
lines changed

README.md

Lines changed: 6 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -668,6 +668,12 @@ We also build on top of many great packages. Please check them out!
668668
- [Differentially Private Gradient Boosting on Linear Learners for Tabular Data Analysis](https://assets.amazon.science/fa/3a/a62ba73f4bbda1d880b678c39193/differentially-private-gradient-boosting-on-linear-learners-for-tabular-data-analysis.pdf)
669669
- [Differentially private and explainable boosting machine with enhanced utility](https://www.sciencedirect.com/science/article/abs/pii/S0925231224011950)
670670
- [Concrete compressive strength prediction using an explainable boosting machine model](https://www.sciencedirect.com/science/article/pii/S2214509523000244/pdfft?md5=171c275b6bcae8897cef03d931e908e2&pid=1-s2.0-S2214509523000244-main.pdf)
671+
- [Assessment of pulse wave velocity through weighted visibility graph metrics from photoplethysmographic signals](https://www.nature.com/articles/s41598-025-16598-x?utm_source=rct_congratemailt&utm_medium=email&utm_campaign=oa_20250826&utm_content=10.1038/s41598-025-16598-x)
672+
- [When Interpretability Meets Generalization: Delta-GAM for Robust Extrapolation in Out-of-Distribution Settings](https://dl.acm.org/doi/pdf/10.1145/3711896.3737180)
673+
- [Interpretable Prediction of Myocardial Infarction Using Explainable Boosting Machines: A Biomarker-Based Machine Learning Approach](https://www.mdpi.com/2075-4418/15/17/2219)
674+
- [Using Explainable Machine Learning to Analyse Expert-Guided Automatic Triage Systems](https://studenttheses.uu.nl/bitstream/handle/20.500.12932/49903/Thomas_vd_Brink_MSc_thesis_2_0-7.pdf?sequence=1&isAllowed=y)
675+
- [Essays on Developing Artificial Intelligence Solutions for Patient centered Healthcare Delivery](https://repositories.lib.utexas.edu/server/api/core/bitstreams/35a2df35-efb6-4a2a-951e-c842814afa9d/content)
676+
- [Mitigating Cognitive Biases in Predicting Student Dropout: Global and Local Explainability with Explainable Boosting Machine](https://www.proquest.com/openview/e4e37e8088593f2db0a9d0e346538ad6/1?pq-origsite=gscholar&cbl=6474026)
671677
- [Proxy endpoints - bridging clinical trials and real world data](https://pdf.sciencedirectassets.com/272371/1-s2.0-S1532046424X00064/1-s2.0-S1532046424001412/main.pdf?X-Amz-Security-Token=IQoJb3JpZ2luX2VjEIn%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEaCXVzLWVhc3QtMSJGMEQCIBYgAN6aOVrDnvQ1932tPndUyJ0Dm1nHdMVLiekPVduQAiAzbYe7W%2Bd6Dj8ee42ZeZnQxJwEjEjuGdiUEPx0a2G43SqyBQgSEAUaDDA1OTAwMzU0Njg2NSIMyMkCUNFeDTCUCppMKo8FiVShykb8phR%2F8aWUGE9gfnE5y7X3Jj1ZA2CVldH13T67s536bdTBhjIMF18rV0YP9iMi6B5aGr%2F286ovIJl332fxZ6iQNBIOPTm8kXQDUqvZbknYldiZqUPs69kuC%2FcKnJd1BWnv2SEZwbRuX94rWnRDPDaSoJx%2FVS6o4qsbFjp9%2BMYZr%2BvJzWHKrXAI4W%2Fh9%2BsIa0yvlac3IMWzAeD23HzDNmF0nqjJ6BSZzmDNW4HRIGBTrTUTO40TzQzhaOY7wyGA0Zv8SpWIULI%2FrY8z8EOX%2FU6OhqgyIMKv%2FSx3rUpMi5CrC1WcpnL97j%2FDAijNi4vMfG1b%2BBQIFRu2EmUky76k4w3FYxkCpYj4n4mk9H%2B%2Bc9C%2BdjKjUiayi%2FisIZUD7ISNhQ9oov0kXI1IVTCGKKQC9jqHOvdiA8YbVuMdEzy1Lkx%2B1kiEo79qvSlpTe2BtWAOm2Iequ01XoaMv%2FQb4ajhWKKSkTafzDAxc58aayP1YH49UzQ68Me7ecdHpx3JUHyYnxJGQ82wRpPkfZJA5wCmOUVI%2FBLuwFJyczG0LpALN5IpIqZz%2B8DvDR0xjRoN49dVwhrTSQ9BesvXbi2LKVm1ptacaaKqyx0PwLjQYKOd%2BPI3zCvRxEiM3IKSNFRLsUTyPNEE4E8pMFNxfyEX59yvTQrHwM62P7hvxHs%2BY6CxUGZTKBQwDAgxttJmiO%2BvjCRbTBXZg1WrQdXCkxntBXb15Mnqxo4lyPzUUkLdLAFK%2BLSwzBIcvSw2qG81Y8qhWmBgBT9vfAoSrjxsILFrB3nnz7u9XNNpRxb5Z9NuNG92%2Fpd%2F%2F5VespMY8Q0iwsNqazZ4M4H8UB34JgtrUEY27WrIsDWzLR%2FAYAxU%2BZHrFzCrsae5BjqyASqDBsNqjEkho%2FbuQDT%2F0vGx%2BgAqrksvVX0GrzNgvqnuPyvw6%2F%2B40ZJP5EA4axfltOYb2tNjd18Ngy2A3cd6J57v1G7wYyuSFIUfHGN5LA8BXK7p0x1mNcwN3pKHtAf260gjpsWMG7anvpK%2F3YupTz498C1lAmurJD%2BLN41lq05wBr403cchE41yzqAKHVKVpNq9s6oGHJmq0KJRvk%2FfjZr8oLhod5gtrwLKvLGqULf50L0%3D&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20241105T092058Z&X-Amz-SignedHeaders=host&X-Amz-Expires=300&X-Amz-Credential=ASIAQ3PHCVTYUKUJCDYI%2F20241105%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=15f8e40964e2c750ae15e43aa8e7f7c76eef6a76b792e41434d14bed42b31432&hash=d4a3e49b29443e5eea9e5a44c0dc11b3f30b21addbe6d6d20d523c68db23cd23&host=68042c943591013ac2b2430a89b270f6af2c76d8dfd086a07176afe7c76c2c61&pii=S1532046424001412&tid=spdf-4fbabbd8-becb-4526-98d3-c7517914e457&sid=8ab2a095350fc74edc4b8765ecd8c0260edcgxrqa&type=client&tsoh=d3d3LnNjaWVuY2VkaXJlY3QuY29t&ua=0f165f0b050207505b0151&rr=8ddbc55a0d60a380&cc=us)
672678
- [Machine Learning Model Reveals Determinators for Admission to Acute Mental Health Wards From Emergency Department Presentations](https://onlinelibrary.wiley.com/doi/epdf/10.1111/inm.13402)
673679
- [Interpretable Machine Learning Models for Predicting Perioperative Myocardial Injury in Non-Cardiac Surgery](https://download.ssrn.com/lancet/3c1e4bc6-9a96-41fe-b60d-4f8c370f9c36-meca.pdf?response-content-disposition=inline&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEFEaCXVzLWVhc3QtMSJGMEQCIHigbeDDkdVUkffH2H2RZYNuuzMq%2FYlkF%2FibCUOmRXZjAiBJ4I7%2BbMuVoMl4APz5MJ9nmLt%2B73WKABFtE2NSd4azJSrGBQiJ%2F%2F%2F%2F%2F%2F%2F%2F%2F%2F8BEAQaDDMwODQ3NTMwMTI1NyIMIVo5lL%2F4nJco3bcLKpoF6PnBkOsbtAPeb6MtFrf4OmMuVjZzVV1Qc6zzBgUTuvijpQFfxzIktRbNW5mUP4fi4rZmjJqhQAjjheSkE7HupPdoBsG3E%2Fii8HKrOXOWErX0qO%2Bwoy%2FFDWS8MdwihFT6EdpwF2yXXAGNz8Vvm%2BgCD772tijc8fXl9DjVtJfr%2BSAPvP3LiG2Pb8UV038Nvko2RbXdyF9rtOmQt1FU738wZ20X3PoLaxzplsAuClhl%2B9zzB5jpC%2BfaW%2BouvPfaZ33McYgKwjTsVv9ox9dBmPgxKbfC%2F5VcF1AAppVeWbGHOj%2BaFIRMocNSaz2IFv06tAqOk7UlIp3p9u4VP8dZ77hf4NI94UEZYojH%2FL%2F6Y23RPj7KtFPjCrHiRbdjaO%2Fl80SoTl21rd41HMBtH%2F%2B%2Fsc5Hgphz9QfI69n03iQ0D6vx30p0knKdwnghrJYYOyW4yCkyztwyYrcOsTOZOcWdvnoGFe6bvIi4DxPrEnf%2FyKDH5iWNeBx5ZAFxzi1ibP8NAXY8c%2B6rr%2Bpe8VGG4shAkI1JRae%2BakvlbBQYbj8vAuVUAGVqM1u8lo0%2FeGfW89KrlojE1VLBUidGrIZSFjCLJP0cG%2FDUbOs7atV1X1H8ny4F5wIw9g0h4lPjj%2FB4vjYPhw%2BOcZYSWiwn1dI0UGNJTyD%2FRtVjuGHT19MOIoqpjSXBymTmOVFjYPSrBYKUUYVfbmzTlrODFwL3oxQwA5eJvAUs0XjXD1rqHQ%2FfISGck5RmCrNlMwpirxgKarRIFwDbzVX8Z7EjTdvIWNAoJJDhwNQCfkdpo12QoINi8yZuiEzdVwMka2sRfIDSyKcn3z2%2B2T6KLgtVf8Q%2BhecxbHgIy8dvcf8secsrh5SDlTia5np%2BNDGLsStb54VQ3oOXMJbE0cQGOrIBoW0oHhskfPiIYI34pCU9cirMG0P9uUmNXP0aJczLXK0mPViF2dAlTOu2uIfl6bFLewWrg7ESDste8Gx6Qci8o4d6rK7ROJv1UpXh9xPRfOx3dksHGKkcW%2FlE4xxEtQ2ctZOSAycoEpPplq4tLgW6BIuDBVR2VxIjY1o5oN7loo13exU4hkJpketet9gRQHdzFYHJYWTzpXDys2TBAp587w2ueQEbnh6zC8GJuv1DxH4OVw%3D%3D&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20250807T093300Z&X-Amz-SignedHeaders=host&X-Amz-Expires=300&X-Amz-Credential=ASIAUPUUPRWEUFEGH3IY%2F20250807%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=1ebccc377c0fbab66bb37e6aac8ab4b50cb82328871b5e8d2b651370d49a58e6&abstractId=5379891)

0 commit comments

Comments
 (0)