Fetching the paper…
Reading the bibliography…
Hundreds of millions of surgical procedures take place annually across the world, which generate a prevalent type of electronic health record (EHR) data comprising time series physiological signals.
“Revisiting self-supervised visual representation learning”
Alexander Kolesnikov, Xiaohua Zhai and Lucas Beyer · 1929
Earlier work this paper cites.
“Circulatory adaptations in hypoxia”
PI Korner · 1959
Earlier work this paper cites.
“Some adverse physiological effects of hypocarbia and methods of maintaining normocarbia during controlled ventilation—a review”
Brian Pollard and David Gibb · 1977
Earlier work this paper cites.
“High inflation pressure pulmonary edema: respective effects of high airway pressure, high tidal volume, and positive end-expiratory pressure”
Didier Dreyfuss, Paul Soler, Guy Basset and Georges Saumon · 1988
Earlier work this paper cites.
“Effect of tidal volume on gas exchange and oxygen transport in the adult respiratory distress syndrome”
Ritva Kiiski, Jukka Takala, Aarno Kari and J Milic-Emili · 1992
Earlier work this paper cites.
“Associations between heart rate and other risk factors in a large French population”
Jean-François Morcet et al · 1999
Earlier work this paper cites.
“Adverse effects of limited hypotensive anesthesia on the outcome of patients with subarachnoid hemorrhage”
Han Chang, Kazuhiro Hongo and Hiroshi Nakagawa · 2000
Earlier work this paper cites.
“Relation between perioperative hypertension and intracranial hemorrhage after craniotomy”
Ayman Basali, Edward Mascha, Iain Kalfas and Armin Schubert · 2000
Earlier work this paper cites.
“Learning to forget: Continual prediction with LSTM”
Felix. Gers, Jurgen Schmidhuber and Fred Cummins · 2000
Earlier work this paper cites.
“Adverse events in surgical patients in Australia”
AK Kable, RW Gibberd and AD Spigelman · 2002
Earlier work this paper cites.
“Harbingers of poor outcome the day after severe brain injury: hypothermia, hypoxia, and hypoperfusion”
Elan Jeremitsky et al · 2003
Earlier work this paper cites.
“Prophylactic phenylephrine infusion for preventing hypotension during spinal anesthesia for cesarean delivery”
Warwick Kee, Kim Khaw, Floria Ng and Bee Lee · 2004
Earlier work this paper cites.
“Survey of anesthesia-related mortality in France”
Andre Lienhart et al · 2006
Earlier work this paper cites.
“The relationship between Precision-Recall and ROC curves”
Jesse Davis and Mark Goadrich · 2006
Earlier work this paper cites.
“Self-taught learning: transfer learning from unlabeled data”
Rajat Raina et al · 2007
Earlier work this paper cites.
“Perioperative hypertension management”
Joseph Varon and Paul Marik · 2008
Earlier work this paper cites.
“The incidence of hypoxemia during surgery: evidence from two institutions”
Jesse Ehrenfeld et al · 2010
Earlier work this paper cites.
“The incidence, root-causes, and outcomes of adverse events in surgical units: implication for potential prevention strategies”
Marieke Zegers et al · 2011
Earlier work this paper cites.
“Domain adaptation for large-scale sentiment classification: A deep learning approach”
Xavier Glorot, Antoine Bordes and Yoshua Bengio · 2011
Cited alongside, same era.
“Role of elevated heart rate in the development of cardiovascular disease in hypertension”
Paolo Palatini · 2011
Cited alongside, same era.
“An overview of health forecasting”
Ireneous Soyiri and Daniel Reidpath · 2013
Cited alongside, same era.
“Transfer learning based clinical concept extraction on data from multiple sources” Special Section: Methods in Clinical Research Informatics
Xinbo Lv, Yi Guan and Benyang Deng · 2014
Cited alongside, same era.
“Creating value in health care through big data: opportunities and policy implications”
Joachim Roski, George Bo-Linn and Timothy Andrews · 2014
Cited alongside, same era.
“How transferable are features in deep neural networks?”
“Surgeries in Hospital-Based Ambulatory Surgery and Hospital Inpatient Settings, 2014”
Claudia. Steiner et al · 2017
Later among the works it cites.
“Wearable sensors for remote health monitoring”
Sumit Majumder, Tapas Mondal and M Deen · 2017
Later among the works it cites.
“TimeNet: Pre-trained deep recurrent neural network for time series classification”
Pankaj Malhotra et al · 2017
Later among the works it cites.
“Medical image data and datasets in the era of machine learning—whitepaper from the 2016 C-MIMI meeting dataset session”
Marc Kohli, Ronald Summers and J Geis · 2017
Later among the works it cites.
“Towards a rigorous science of interpretable machine learning”
Finale Doshi-Velez and Been Kim · 2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Jason Yosinski, Jeff Clune, Yoshua Bengio and Hod Lipson · 2014
Cited alongside, same era.
“Optimal perioperative management of arterial blood pressure”
Laurent Lonjaret, Olivier Lairez, Vincent Minville and Thomas Geeraerts · 2014
Cited alongside, same era.
“Model inversion attacks that exploit confidence information and basic countermeasures”
Matt Fredrikson, Somesh Jha and Thomas Ristenpart · 2015
Cited alongside, same era.
“Size and distribution of the global volume of surgery in 2012”
Thomas Weiser et al · 2016
Cited alongside, same era.
“Preventable adverse events in surgical care in Sweden: a nationwide review of patient notes”
Lena Nilsson et al · 2016
Cited alongside, same era.
“An All-Payer View of Hospital Discharge to Postacute Care, 2013”
Tian Wen · 2016
Cited alongside, same era.
“Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?”
N. Tajbakhsh et al · 2016
Cited alongside, same era.
Alexis Conneau et al · 2017
Later among the works it cites.
“A unified approach to interpreting model predictions”
Scott Lundberg and Su-In Lee · 2017
Later among the works it cites.
“Inter-subject transfer learning with end-to-end deep convolutional neural network for EEG-based BCI”
Fatemeh Fahimi et al · 2018
Later among the works it cites.
“Explainable machine-learning predictions for the prevention of hypoxaemia during surgery”
Scott Lundberg et al · 2018
Later among the works it cites.
“ECG arrhythmia classification using transfer learning from 2-dimensional deep CNN features”
Milad Salem, Shayan Taheri and Jiann–Shiun Yuan · 2018
Later among the works it cites.
“A novel application of deep learning for single-lead ECG classification”
Sherin Mathews, Chandra Kambhamettu and Kenneth Barner · 2018
Later among the works it cites.
“A deep learning approach for Parkinson’s disease diagnosis from EEG signals”
Shu Oh et al · 2018
Later among the works it cites.
“A review of big data applications of physiological signal data”
Christina Orphanidou · 2019
Later among the works it cites.
“Transfer Learning for Clinical Time Series Analysis using Deep Neural Networks”
Priyanka Gupta et al · 2019
Later among the works it cites.
“From local explanations to global understanding with explainable AI for trees”
Scott Lundberg et al · 2020
Closest in time.
“Predicting the efficiency of prime editing guide RNAs in human cells”
Hui Kim et al · 2020
Closest in time.
“Machine Learning Algorithms for Predicting and Risk Profiling of Cardiac Surgery-Associated Acute Kidney Injury”
Jahan Penny-Dimri et al · 2020
Closest in time.
“Predicting modality in financial dialogue”
Kilian Theil and Heiner Stuckenschmidt · 2020
Closest in time.