| Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI B Vasey, M Nagendran, B Campbell, DA Clifton, GS Collins, S Denaxas, ... bmj 377, 2022 | 231 | 2022 |
| Systematic review and comparison of publicly available ICU data sets—a decision guide for clinicians and data scientists CM Sauer, TA Dam, LA Celi, M Faltys, MAA de la Hoz, L Adhikari, ... Critical care medicine 50 (6), e581-e588, 2022 | 49 | 2022 |
| Temporal trends in critical care outcomes in US minority-serving hospitals J Danziger, M Ángel Armengol de la Hoz, W Li, M Komorowski, ... American journal of respiratory and critical care medicine 201 (6), 681-687, 2020 | 46 | 2020 |
| Big data analysis and machine learning in intensive care units AN Reiz, MAA de la Hoz, MS García Medicina Intensiva (English Edition) 43 (7), 416-426, 2019 | 39 | 2019 |
| Big data and machine learning in critical care: Opportunities for collaborative research OC of the Madrid, AN Reiz, FM Sagasti, MÁ González, AB Malpica, ... Medicina intensiva 43 (1), 52-57, 2019 | 33 | 2019 |
| Intraoperative hypotension and acute kidney injury, stroke, and mortality during and outside cardiopulmonary bypass: a retrospective observational cohort study MA De La Hoz, V Rangasamy, AB Bastos, X Xu, V Novack, B Saugel, ... Anesthesiology 136 (6), 927-939, 2022 | 32 | 2022 |
| Big Data Analysis and Machine Learning in Intensive Care Units. A Núñez Reiz, MA Armengol de la Hoz, M Sánchez García | 29 | 2018 |
| Developing well-calibrated illness severity scores for decision support in the critically ill CV Cosgriff, LA Celi, S Ko, T Sundaresan, MÁ Armengol de la Hoz, ... NPJ digital medicine 2 (1), 76, 2019 | 26 | 2019 |
| Machine learning models with preoperative risk factors and intraoperative hypotension parameters predict mortality after cardiac surgery MPB Fernandes, MA de la Hoz, V Rangasamy, B Subramaniam Journal of Cardiothoracic and Vascular Anesthesia 35 (3), 857-865, 2021 | 25 | 2021 |
| Assessing team effectiveness and affective learning in a datathon FM de Toledo Piza, LA Celi, RO Deliberato, L Bulgarelli, FRT de Carvalho, ... International journal of medical informatics 112, 40-44, 2018 | 23 | 2018 |
| Severity of illness scores may misclassify critically ill obese patients RO Deliberato, S Ko, M Komorowski, MAA de La Hoz, MP Frushicheva, ... Critical care medicine 46 (3), 394-400, 2018 | 22 | 2018 |
| A guide to sharing open healthcare data under the General Data Protection Regulation JWTM de Kok, MÁA de la Hoz, Y de Jong, V Brokke, PWG Elbers, ... Scientific data 10 (1), 404, 2023 | 17 | 2023 |
| Incidence and risk model development for severe tachypnea following terminal extubation CR Fehnel, MA de la Hoz, LA Celi, ML Campbell, K Hanafy, A Nozari, ... Chest 158 (4), 1456-1463, 2020 | 11 | 2020 |
| Association of chloride ion and sodium-chloride difference with acute kidney injury and mortality in critically ill patients S Kimura, MAA De La Hoz, NH Raines, LA Celi Critical care explorations 2 (12), e0247, 2020 | 10 | 2020 |
| A novel Vascular Leak Index identifies sepsis patients with a higher risk for in-hospital death and fluid accumulation J Chandra, MA Armengol de la Hoz, G Lee, A Lee, P Thoral, P Elbers, ... Critical Care 26 (1), 103, 2022 | 9 | 2022 |
| First Brazilian datathon in critical care A Serpa Neto, G Kugener, L Bulgarelli, R Rabello Filho, MÁA Hoz, ... Revista Brasileira de terapia intensiva 30, 6-8, 2018 | 8 | 2018 |
| Metabolic cost of exercise initiation in patients with heart failure with preserved ejection fraction vs community-dwelling adults RV Shah, MW Schoenike, MÁA de la Hoz, TF Cunningham, JB Blodgett, ... JAMA cardiology 6 (6), 653-660, 2021 | 7 | 2021 |
| Use of Do-Not-Resuscitate orders for critically ill patients with ESKD J Danziger, MÁA de la Hoz, LA Celi, RA Cohen, KJ Mukamal Journal of the American Society of Nephrology 31 (10), 2393-2399, 2020 | 7 | 2020 |
| A large-scale multicenter retrospective study on nephrotoxicity associated with empiric broad-spectrum antibiotics in critically ill patients AY Chen, CY Deng, P Calvachi-Prieto, MÁA de la Hoz, A Khazi-Syed, ... Chest 164 (2), 355-368, 2023 | 6 | 2023 |
| Predicting ICU mortality in Acute Respiratory Distress Syndrome patients using machine learning: the Predicting Outcome and STratifiCation of severity in ARDS (POSTCARDS) Study J Villar, JM González-Martín, J Hernández-González, MA Armengol, ... Critical care medicine 51 (12), 1638-1649, 2023 | 5 | 2023 |
Leo Anthony CeliMassachusetts Institute of TechnologyVerified email at mit.edu
