A citation-based method for searching scientific literature

Annelaura B Nielsen, Hans-Christian Thorsen-Meyer, Kirstine Belling, Anna P Nielsen, Cecilia E Thomas, Piotr J Chmura, Mette Lademann, Pope L Moseley, Marc Heimann, Lars Dybdahl, Lasse Spangsege, Patrick Hulsen, Anders Perner, Søren Brunak. Lancet Digit Health 2019
Times Cited: 29







List of co-cited articles
279 articles co-cited >1



Times Cited
  Times     Co-cited
Similarity


Making Machine Learning Models Clinically Useful.
Nigam H Shah, Arnold Milstein, Steven C Bagley PhD. JAMA 2019
52
13

Scalable and accurate deep learning with electronic health records.
Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M Dai, Nissan Hajaj, Michaela Hardt, Peter J Liu, Xiaobing Liu, Jake Marcus, Mimi Sun,[...]. NPJ Digit Med 2018
453
13


Ensuring Fairness in Machine Learning to Advance Health Equity.
Alvin Rajkomar, Michaela Hardt, Michael D Howell, Greg Corrado, Marshall H Chin. Ann Intern Med 2018
100
13

A guide to deep learning in healthcare.
Andre Esteva, Alexandre Robicquet, Bharath Ramsundar, Volodymyr Kuleshov, Mark DePristo, Katherine Chou, Claire Cui, Greg Corrado, Sebastian Thrun, Jeff Dean. Nat Med 2019
353
13

Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records.
Hans-Christian Thorsen-Meyer, Annelaura B Nielsen, Anna P Nielsen, Benjamin Skov Kaas-Hansen, Palle Toft, Jens Schierbeck, Thomas Strøm, Piotr J Chmura, Marc Heimann, Lars Dybdahl,[...]. Lancet Digit Health 2020
21
19


Mortality prediction in intensive care units with the Super ICU Learner Algorithm (SICULA): a population-based study.
Romain Pirracchio, Maya L Petersen, Marco Carone, Matthieu Resche Rigon, Sylvie Chevret, Mark J van der Laan. Lancet Respir Med 2015
116
10

Big Data and Machine Learning in Health Care.
Andrew L Beam, Isaac S Kohane. JAMA 2018
347
10

The Artificial Intelligence Clinician learns optimal treatment strategies for sepsis in intensive care.
Matthieu Komorowski, Leo A Celi, Omar Badawi, Anthony C Gordon, A Aldo Faisal. Nat Med 2018
203
10

Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review.
Benjamin A Goldstein, Ann Marie Navar, Michael J Pencina, John P A Ioannidis. J Am Med Inform Assoc 2017
213
10

Optimal intensive care outcome prediction over time using machine learning.
Christopher Meiring, Abhishek Dixit, Steve Harris, Niall S MacCallum, David A Brealey, Peter J Watkinson, Andrew Jones, Simon Ashworth, Richard Beale, Stephen J Brett,[...]. PLoS One 2018
23
13

Network biology concepts in complex disease comorbidities.
Jessica Xin Hu, Cecilia Engel Thomas, Søren Brunak. Nat Rev Genet 2016
127
10

Temporal disease trajectories condensed from population-wide registry data covering 6.2 million patients.
Anders Boeck Jensen, Pope L Moseley, Tudor I Oprea, Sabrina Gade Ellesøe, Robert Eriksson, Henriette Schmock, Peter Bjødstrup Jensen, Lars Juhl Jensen, Søren Brunak. Nat Commun 2014
132
10


Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension.
Samantha Cruz Rivera, Xiaoxuan Liu, An-Wen Chan, Alastair K Denniston, Melanie J Calvert. Nat Med 2020
47
10

Machine Learning in Medicine.
Alvin Rajkomar, Jeffrey Dean, Isaac Kohane. N Engl J Med 2019
439
10

Dissecting racial bias in an algorithm used to manage the health of populations.
Ziad Obermeyer, Brian Powers, Christine Vogeli, Sendhil Mullainathan. Science 2019
325
10

Opening the black box of machine learning.
The Lancet Respiratory Medicine. Lancet Respir Med 2018
30
10

DeepSOFA: A Continuous Acuity Score for Critically Ill Patients using Clinically Interpretable Deep Learning.
Benjamin Shickel, Tyler J Loftus, Lasith Adhikari, Tezcan Ozrazgat-Baslanti, Azra Bihorac, Parisa Rashidi. Sci Rep 2019
28
10

A targeted real-time early warning score (TREWScore) for septic shock.
Katharine E Henry, David N Hager, Peter J Pronovost, Suchi Saria. Sci Transl Med 2015
198
10

Key challenges for delivering clinical impact with artificial intelligence.
Christopher J Kelly, Alan Karthikesalingam, Mustafa Suleyman, Greg Corrado, Dominic King. BMC Med 2019
149
10

Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
10

A Systematic Review of Predictions of Survival in Palliative Care: How Accurate Are Clinicians and Who Are the Experts?
Nicola White, Fiona Reid, Adam Harris, Priscilla Harries, Patrick Stone. PLoS One 2016
83
6


An exploration of social and economic outcome and associated health-related quality of life after critical illness in general intensive care unit survivors: a 12-month follow-up study.
John Griffiths, Robert A Hatch, Judith Bishop, Kayleigh Morgan, Crispin Jenkinson, Brian H Cuthbertson, Stephen J Brett. Crit Care 2013
145
6

The status of intensive care medicine research and a future agenda for very old patients in the ICU.
H Flaatten, D W de Lange, A Artigas, D Bin, R Moreno, S Christensen, G M Joynt, Sean M Bagshaw, C L Sprung, D Benoit,[...]. Intensive Care Med 2017
88
6

Functional trajectories among older persons before and after critical illness.
Lauren E Ferrante, Margaret A Pisani, Terrence E Murphy, Evelyne A Gahbauer, Linda S Leo-Summers, Thomas M Gill. JAMA Intern Med 2015
156
6

The contribution of frailty, cognition, activity of daily life and comorbidities on outcome in acutely admitted patients over 80 years in European ICUs: the VIP2 study.
Bertrand Guidet, Dylan W de Lange, Ariane Boumendil, Susannah Leaver, Ximena Watson, Carol Boulanger, Wojciech Szczeklik, Antonio Artigas, Alessandro Morandi, Finn Andersen,[...]. Intensive Care Med 2020
61
6


Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.
Varun Gulshan, Lily Peng, Marc Coram, Martin C Stumpe, Derek Wu, Arunachalam Narayanaswamy, Subhashini Venugopalan, Kasumi Widner, Tom Madams, Jorge Cuadros,[...]. JAMA 2016
6


ICU severity of illness scores: APACHE, SAPS and MPM.
Jorge I F Salluh, Márcio Soares. Curr Opin Crit Care 2014
86
6


Causal inference and the data-fusion problem.
Elias Bareinboim, Judea Pearl. Proc Natl Acad Sci U S A 2016
75
6

Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data.
Jenna M Reps, Martijn J Schuemie, Marc A Suchard, Patrick B Ryan, Peter R Rijnbeek. J Am Med Inform Assoc 2018
38
6

Long short-term memory.
S Hochreiter, J Schmidhuber. Neural Comput 1997
6

Explainable machine-learning predictions for the prevention of hypoxaemia during surgery.
Scott M Lundberg, Bala Nair, Monica S Vavilala, Mayumi Horibe, Michael J Eisses, Trevor Adams, David E Liston, Daniel King-Wai Low, Shu-Fang Newman, Jerry Kim,[...]. Nat Biomed Eng 2018
142
6

Machine Learning and Decision Support in Critical Care.
Alistair E W Johnson, Mohammad M Ghassemi, Shamim Nemati, Katherine E Niehaus, David A Clifton, Gari D Clifford. Proc IEEE Inst Electr Electron Eng 2016
90
6

Assessing the performance of prediction models: a framework for traditional and novel measures.
Ewout W Steyerberg, Andrew J Vickers, Nancy R Cook, Thomas Gerds, Mithat Gonen, Nancy Obuchowski, Michael J Pencina, Michael W Kattan. Epidemiology 2010
6

The Danish National Patient Registry: a review of content, data quality, and research potential.
Morten Schmidt, Sigrun Alba Johannesdottir Schmidt, Jakob Lynge Sandegaard, Vera Ehrenstein, Lars Pedersen, Henrik Toft Sørensen. Clin Epidemiol 2015
6

Population-wide analysis of differences in disease progression patterns in men and women.
David Westergaard, Pope Moseley, Freja Karuna Hemmingsen Sørup, Pierre Baldi, Søren Brunak. Nat Commun 2019
34
6

How to Read Articles That Use Machine Learning: Users' Guides to the Medical Literature.
Yun Liu, Po-Hsuan Cameron Chen, Jonathan Krause, Lily Peng. JAMA 2019
115
6

A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis.
Xiaoxuan Liu, Livia Faes, Aditya U Kale, Siegfried K Wagner, Dun Jack Fu, Alice Bruynseels, Thushika Mahendiran, Gabriella Moraes, Mohith Shamdas, Christoph Kern,[...]. Lancet Digit Health 2019
178
6

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension.
Xiaoxuan Liu, Samantha Cruz Rivera, David Moher, Melanie J Calvert, Alastair K Denniston. Nat Med 2020
62
6

A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice.
Heather M Giannini, Jennifer C Ginestra, Corey Chivers, Michael Draugelis, Asaf Hanish, William D Schweickert, Barry D Fuchs, Laurie Meadows, Michael Lynch, Patrick J Donnelly,[...]. Crit Care Med 2019
48
6

Assessment of Clinical Criteria for Sepsis: For the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3).
Christopher W Seymour, Vincent X Liu, Theodore J Iwashyna, Frank M Brunkhorst, Thomas D Rea, André Scherag, Gordon Rubenfeld, Jeremy M Kahn, Manu Shankar-Hari, Mervyn Singer,[...]. JAMA 2016
6

APACHE II: a severity of disease classification system.
W A Knaus, E A Draper, D P Wagner, J E Zimmerman. Crit Care Med 1985
6

Artificial intelligence in the intensive care unit.
Christopher A Lovejoy, Varun Buch, Mahiben Maruthappu. Crit Care 2019
15
13

Predicting Mortality of Patients With Sepsis: A Comparison of APACHE II and APACHE III Scoring Systems.
Farid Sadaka, Cheikh EthmaneAbouElMaali, Margaret A Cytron, Kimberly Fowler, Victoria M Javaux, Jacklyn O'Brien. J Clin Med Res 2017
19
10


Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.