| Economic impacts of non-native forest insects in the continental United States JE Aukema, B Leung, K Kovacs, C Chivers, KO Britton, J Englin, ... PLoS one 6 (9), e24587, 2011 | 673 | 2011 |
| Locally informed simulation to predict hospital capacity needs during the COVID-19 pandemic GE Weissman, A Crane-Droesch, C Chivers, TB Luong, A Hanish, ... Annals of internal medicine 173 (1), 21-28, 2020 | 334 | 2020 |
| A reinforcement learning approach to weaning of mechanical ventilation in intensive care units N Prasad, LF Cheng, C Chivers, M Draugelis, BE Engelhardt arXiv preprint arXiv:1704.06300, 2017 | 211 | 2017 |
| A machine learning algorithm to predict severe sepsis and septic shock: development, implementation, and impact on clinical practice HM Giannini, JC Ginestra, C Chivers, M Draugelis, A Hanish, ... Critical care medicine 47 (11), 1485-1492, 2019 | 200 | 2019 |
| Machine learning approaches to predict 6-month mortality among patients with cancer RB Parikh, C Manz, C Chivers, SH Regli, J Braun, ME Draugelis, ... JAMA network open 2 (10), e1915997-e1915997, 2019 | 188 | 2019 |
| Clinician perception of a machine learning–based early warning system designed to predict severe sepsis and septic shock JC Ginestra, HM Giannini, WD Schweickert, L Meadows, MJ Lynch, ... Critical care medicine 47 (11), 1477-1484, 2019 | 134 | 2019 |
| Effect of integrating machine learning mortality estimates with behavioral nudges to clinicians on serious illness conversations among patients with cancer: a stepped-wedge … CR Manz, RB Parikh, DS Small, CN Evans, C Chivers, SH Regli, ... JAMA oncology 6 (12), e204759-e204759, 2020 | 115 | 2020 |
| Sparse multi-output Gaussian processes for online medical time series prediction LF Cheng, B Dumitrascu, G Darnell, C Chivers, M Draugelis, K Li, ... BMC medical informatics and decision making 20, 1-23, 2020 | 95 | 2020 |
| Validation of a machine learning algorithm to predict 180-day mortality for outpatients with cancer CR Manz, J Chen, M Liu, C Chivers, SH Regli, J Braun, M Draugelis, ... JAMA oncology 6 (11), 1723-1730, 2020 | 87 | 2020 |
| Rising complexity and falling explanatory power in ecology E Low-Décarie, C Chivers, M Granados Frontiers in Ecology and the Environment 12 (7), 412-418, 2014 | 83 | 2014 |
| Electronic health record mortality prediction model for targeted palliative care among hospitalized medical patients: a pilot quasi-experimental study KR Courtright, C Chivers, M Becker, SH Regli, LC Pepper, ME Draugelis, ... Journal of general internal medicine 34, 1841-1847, 2019 | 65 | 2019 |
| Trends and focus of machine learning applications for health research B Beaulieu-Jones, SG Finlayson, C Chivers, I Chen, M McDermott, ... JAMA network open 2 (10), e1914051-e1914051, 2019 | 62 | 2019 |
| Importing risk: quantifying the propagule pressure–establishment relationship at the pathway level J Bradie, C Chivers, B Leung Diversity and Distributions 19 (8), 1020-1030, 2013 | 53 | 2013 |
| MHadaptive: general Markov Chain Monte Carlo for Bayesian inference using adaptive Metropolis-Hastings sampling C Chivers R package version, 2012 | 53 | 2012 |
| Long-term effect of machine learning–triggered behavioral Nudges on serious illness conversations and end-of-life outcomes among patients with cancer: A randomized clinical trial CR Manz, Y Zhang, K Chen, Q Long, DS Small, CN Evans, C Chivers, ... JAMA oncology 9 (3), 414-418, 2023 | 40 | 2023 |
| Predicting invasions: alternative models of human‐mediated dispersal and interactions between dispersal network structure and A llee effects C Chivers, B Leung Journal of Applied Ecology 49 (5), 1113-1123, 2012 | 33 | 2012 |
| Clinical impact of an electronic dashboard and alert system for sedation minimization and ventilator liberation: a before-after study BJ Anderson, D Do, C Chivers, K Choi, Y Gitelman, SJ Mehta, ... Critical care explorations 1 (10), e0057, 2019 | 21 | 2019 |
| Application of machine learning approaches to administrative claims data to predict clinical outcomes in medical and surgical patient populations EJ MacKay, MD Stubna, C Chivers, ME Draugelis, WJ Hanson, ND Desai, ... PLoS One 16 (6), e0252585, 2021 | 19 | 2021 |
| Validation and calibration of probabilistic predictions in ecology C Chivers, B Leung, ND Yan Methods in Ecology and Evolution 5 (10), 1023-1032, 2014 | 15 | 2014 |
| Using electronic health records and claims data to identify high-risk patients likely to benefit from palliative care. A Guo, R Foraker, P White, C Chivers, K Courtright, N Moore American Journal of Managed Care 27 (1), 2021 | 14 | 2021 |
Robert G HaightUS Forest Service Northern Research Station在 fs.fed.us 的电子邮件经过验证
