Detalhe da pesquisa
1.
Machine learning clinical prediction models for acute kidney injury: the impact of baseline creatinine on prediction efficacy.
BMC Med Inform Decis Mak
; 23(1): 207, 2023 10 09.
Artigo
em Inglês
| MEDLINE | ID: mdl-37814311
2.
Physical Grounds for Causal Perspectivalism.
Entropy (Basel)
; 25(8)2023 Aug 10.
Artigo
em Inglês
| MEDLINE | ID: mdl-37628219
3.
Use of an extended KDIGO definition to diagnose acute kidney injury in patients with COVID-19: A multinational study using the ISARIC-WHO clinical characterisation protocol.
PLoS Med
; 19(4): e1003969, 2022 04.
Artigo
em Inglês
| MEDLINE | ID: mdl-35442972
4.
Early short course of neuromuscular blocking agents in patients with COVID-19 ARDS: a propensity score analysis.
Crit Care
; 26(1): 141, 2022 05 17.
Artigo
em Inglês
| MEDLINE | ID: mdl-35581612
5.
An appraisal of respiratory system compliance in mechanically ventilated covid-19 patients.
Crit Care
; 25(1): 199, 2021 06 09.
Artigo
em Inglês
| MEDLINE | ID: mdl-34108029
6.
Classical and Quantum Causal Interventions.
Entropy (Basel)
; 20(9)2018 Sep 08.
Artigo
em Inglês
| MEDLINE | ID: mdl-33265776
7.
Systematic review of externally validated machine learning models for predicting acute kidney injury in general hospital patients.
Front Nephrol
; 3: 1220214, 2023.
Artigo
em Inglês
| MEDLINE | ID: mdl-37675372
8.
Association of Country Income Level With the Characteristics and Outcomes of Critically Ill Patients Hospitalized With Acute Kidney Injury and COVID-19.
Kidney Int Rep
; 2023 May 27.
Artigo
em Inglês
| MEDLINE | ID: mdl-37360820
9.
A multi-country analysis of COVID-19 hospitalizations by vaccination status.
Med
; 4(11): 797-812.e2, 2023 11 10.
Artigo
em Inglês
| MEDLINE | ID: mdl-37738979
10.
Machine learning models for diabetes management in acute care using electronic medical records: A systematic review.
Int J Med Inform
; 162: 104758, 2022 Apr 02.
Artigo
em Inglês
| MEDLINE | ID: mdl-35398812
11.
Toward a Learning Health Care System: A Systematic Review and Evidence-Based Conceptual Framework for Implementation of Clinical Analytics in a Digital Hospital.
Appl Clin Inform
; 13(2): 339-354, 2022 03.
Artigo
em Inglês
| MEDLINE | ID: mdl-35388447
12.
ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19.
Sci Data
; 9(1): 454, 2022 07 30.
Artigo
em Inglês
| MEDLINE | ID: mdl-35908040
13.
Clinical characteristics, risk factors and outcomes in patients with severe COVID-19 registered in the International Severe Acute Respiratory and Emerging Infection Consortium WHO clinical characterisation protocol: a prospective, multinational, multicentre, observational study.
ERJ Open Res
; 8(1)2022 Jan.
Artigo
em Inglês
| MEDLINE | ID: mdl-35169585
14.
Intensive care digital health response to emerging infectious disease outbreaks such as COVID-19.
Anaesth Intensive Care
; 49(2): 105-111, 2021 Mar.
Artigo
em Inglês
| MEDLINE | ID: mdl-33504171
15.
International Society of Nephrology Global Kidney Health Atlas: structures, organization, and services for the management of kidney failure in Latin America.
Kidney Int Suppl (2011)
; 11(2): e35-e46, 2021 May.
Artigo
em Inglês
| MEDLINE | ID: mdl-33981469
16.
Assessment of 28-Day In-Hospital Mortality in Mechanically Ventilated Patients With Coronavirus Disease 2019: An International Cohort Study.
Crit Care Explor
; 3(11): e0567, 2021 Nov.
Artigo
em Inglês
| MEDLINE | ID: mdl-34765979
17.
Design and rationale of the COVID-19 Critical Care Consortium international, multicentre, observational study.
BMJ Open
; 10(12): e041417, 2020 12 02.
Artigo
em Inglês
| MEDLINE | ID: mdl-33268426