These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
129 related articles for article (PubMed ID: 38166918)
1. Development and evaluation of regression tree models for predicting in-hospital mortality of a national registry of COVID-19 patients over six pandemic surges. Schut MC; Dongelmans DA; de Lange DW; Brinkman S; ; de Keizer NF; Abu-Hanna A BMC Med Inform Decis Mak; 2024 Jan; 24(1):7. PubMed ID: 38166918 [TBL] [Abstract][Full Text] [Related]
2. Can we reliably automate clinical prognostic modelling? A retrospective cohort study for ICU triage prediction of in-hospital mortality of COVID-19 patients in the Netherlands. Vagliano I; Brinkman S; Abu-Hanna A; Arbous MS; Dongelmans DA; Elbers PWG; de Lange DW; van der Schaar M; de Keizer NF; Schut MC; Int J Med Inform; 2022 Apr; 160():104688. PubMed ID: 35114522 [TBL] [Abstract][Full Text] [Related]
3. 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. Thorsen-Meyer HC; Nielsen AB; Nielsen AP; Kaas-Hansen BS; Toft P; Schierbeck J; Strøm T; Chmura PJ; Heimann M; Dybdahl L; Spangsege L; Hulsen P; Belling K; Brunak S; Perner A Lancet Digit Health; 2020 Apr; 2(4):e179-e191. PubMed ID: 33328078 [TBL] [Abstract][Full Text] [Related]
4. COVID outcome prediction in the emergency department (COPE): using retrospective Dutch hospital data to develop simple and valid models for predicting mortality and need for intensive care unit admission in patients who present at the emergency department with suspected COVID-19. van Klaveren D; Rekkas A; Alsma J; Verdonschot RJCG; Koning DTJJ; Kamps MJA; Dormans T; Stassen R; Weijer S; Arnold KS; Tomlow B; de Geus HRH; van Bruchem-Visser RL; Miedema JR; Verbon A; van Nood E; Kent DM; Schuit SCE; Lingsma H BMJ Open; 2021 Sep; 11(9):e051468. PubMed ID: 34531219 [TBL] [Abstract][Full Text] [Related]
5. Assess and validate predictive performance of models for in-hospital mortality in COVID-19 patients: A retrospective cohort study in the Netherlands comparing the value of registry data with high-granular electronic health records. Vagliano I; Schut MC; Abu-Hanna A; Dongelmans DA; de Lange DW; Gommers D; Cremer OL; Bosman RJ; Rigter S; Wils EJ; Frenzel T; de Jong R; Peters MAA; Kamps MJA; Ramnarain D; Nowitzky R; Nooteboom FGCA; de Ruijter W; Urlings-Strop LC; Smit EGM; Mehagnoul-Schipper DJ; Dormans T; de Jager CPC; Hendriks SHA; Achterberg S; Oostdijk E; Reidinga AC; Festen-Spanjer B; Brunnekreef GB; Cornet AD; van den Tempel W; Boelens AD; Koetsier P; Lens J; Faber HJ; Karakus A; Entjes R; de Jong P; Rettig TCD; Reuland MC; Arbous S; Fleuren LM; Dam TA; Thoral PJ; Lalisang RCA; Tonutti M; de Bruin DP; Elbers PWG; de Keizer NF; Int J Med Inform; 2022 Nov; 167():104863. PubMed ID: 36162166 [TBL] [Abstract][Full Text] [Related]
6. Survival prediction in intensive-care units based on aggregation of long-term disease history and acute physiology: a retrospective study of the Danish National Patient Registry and electronic patient records. Nielsen AB; Thorsen-Meyer HC; Belling K; Nielsen AP; Thomas CE; Chmura PJ; Lademann M; Moseley PL; Heimann M; Dybdahl L; Spangsege L; Hulsen P; Perner A; Brunak S Lancet Digit Health; 2019 Jun; 1(2):e78-e89. PubMed ID: 33323232 [TBL] [Abstract][Full Text] [Related]
7. Prediction model and risk scores of ICU admission and mortality in COVID-19. Zhao Z; Chen A; Hou W; Graham JM; Li H; Richman PS; Thode HC; Singer AJ; Duong TQ PLoS One; 2020; 15(7):e0236618. PubMed ID: 32730358 [TBL] [Abstract][Full Text] [Related]
8. Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone. Lee CC; Chen CW; Yen HK; Lin YP; Lai CY; Wang JL; Groot OQ; Janssen SJ; Schwab JH; Hsu FM; Lin WH Clin Orthop Relat Res; 2024 Dec; 482(12):2193-2208. PubMed ID: 39051924 [TBL] [Abstract][Full Text] [Related]
9. Predicting 30-day mortality in intensive care unit patients with ischaemic stroke or intracerebral haemorrhage. van Valburg MK; Termorshuizen F; Geerts BF; Abdo WF; van den Bergh WM; Brinkman S; Horn J; van Mook WNKA; Slooter AJC; Wermer MJH; Siegerink B; Arbous MS Eur J Anaesthesiol; 2024 Feb; 41(2):136-145. PubMed ID: 37962175 [TBL] [Abstract][Full Text] [Related]
10. Development and validation of a prognostic model based on comorbidities to predict COVID-19 severity: a population-based study. Gude-Sampedro F; Fernández-Merino C; Ferreiro L; Lado-Baleato Ó; Espasandín-Domínguez J; Hervada X; Cadarso CM; Valdés L Int J Epidemiol; 2021 Mar; 50(1):64-74. PubMed ID: 33349845 [TBL] [Abstract][Full Text] [Related]
11. Characterising risk of in-hospital mortality following cardiac arrest using machine learning: A retrospective international registry study. Nanayakkara S; Fogarty S; Tremeer M; Ross K; Richards B; Bergmeir C; Xu S; Stub D; Smith K; Tacey M; Liew D; Pilcher D; Kaye DM PLoS Med; 2018 Nov; 15(11):e1002709. PubMed ID: 30500816 [TBL] [Abstract][Full Text] [Related]
12. Development and external validation of prognostic models for COVID-19 to support risk stratification in secondary care. Adderley NJ; Taverner T; Price MJ; Sainsbury C; Greenwood D; Chandan JS; Takwoingi Y; Haniffa R; Hosier I; Welch C; Parekh D; Gallier S; Gokhale K; Denniston AK; Sapey E; Nirantharakumar K BMJ Open; 2022 Jan; 12(1):e049506. PubMed ID: 35039282 [TBL] [Abstract][Full Text] [Related]
13. Machine Learning Did Not Outperform Conventional Competing Risk Modeling to Predict Revision Arthroplasty. Oosterhoff JHF; de Hond AAH; Peters RM; van Steenbergen LN; Sorel JC; Zijlstra WP; Poolman RW; Ring D; Jutte PC; Kerkhoffs GMMJ; Putter H; Steyerberg EW; Doornberg JN; Clin Orthop Relat Res; 2024 Aug; 482(8):1472-1482. PubMed ID: 38470976 [TBL] [Abstract][Full Text] [Related]
14. Construction and evaluation of a mortality prediction model for patients with acute kidney injury undergoing continuous renal replacement therapy based on machine learning algorithms. Wang Y; Sun X; Lu J; Zhong L; Yang Z Ann Med; 2024 Dec; 56(1):2388709. PubMed ID: 39155811 [TBL] [Abstract][Full Text] [Related]
15. Development of the Combined Assessment of Risk Encountered in Surgery (CARES) surgical risk calculator for prediction of postsurgical mortality and need for intensive care unit admission risk: a single-center retrospective study. Chan DXH; Sim YE; Chan YH; Poopalalingam R; Abdullah HR BMJ Open; 2018 Mar; 8(3):e019427. PubMed ID: 29574442 [TBL] [Abstract][Full Text] [Related]
16. A first-level customization study of SAPS II with Norwegian Intensive Care and Pandemic Registry (NIPaR) data. Bruserud Ø; Haaland ØA; Kvåle R; Buanes EA Acta Anaesthesiol Scand; 2023 Jul; 67(6):772-778. PubMed ID: 36906805 [TBL] [Abstract][Full Text] [Related]
17. Identification of high-risk subgroups in very elderly intensive care unit patients. de Rooij SE; Abu-Hanna A; Levi M; de Jonge E Crit Care; 2007; 11(2):R33. PubMed ID: 17346348 [TBL] [Abstract][Full Text] [Related]
18. Predicting Mortality in Low-Income Country ICUs: The Rwanda Mortality Probability Model (R-MPM). Riviello ED; Kiviri W; Fowler RA; Mueller A; Novack V; Banner-Goodspeed VM; Weinkauf JL; Talmor DS; Twagirumugabe T PLoS One; 2016; 11(5):e0155858. PubMed ID: 27196252 [TBL] [Abstract][Full Text] [Related]