Seneviratne MG - Search Results

1

Development and Implementation of a Real-time Bundle-adherence Dashboard for Central Line-associated Bloodstream Infections.

Chemparathy A, Seneviratne MG, Ward A, Mirchandani S, Li R, Mathew R, Wood M, Shin AY, Donnelly LF, Scheinker D, Lee GM. Chemparathy A, et al. Among authors: seneviratne mg. Pediatr Qual Saf. 2021 Jun 23;6(4):e431. doi: 10.1097/pq9.0000000000000431. eCollection 2021 Jul-Aug. Pediatr Qual Saf. 2021. PMID: 34235355 Free PMC article.

2

The Association Between Central Line-Associated Bloodstream Infection and Central Line Access.

Ward A, Chemparathy A, Seneviratne M, Gaskari S, Mathew R, Wood M, Donnelly LF, Lee GM, Scheinker D, Shin AY. Ward A, et al. Crit Care Med. 2023 Jun 1;51(6):787-796. doi: 10.1097/CCM.0000000000005838. Epub 2023 Mar 15. Crit Care Med. 2023. PMID: 36920081

3

Architecture and Implementation of a Clinical Research Data Warehouse for Prostate Cancer.

Seneviratne MG, Seto T, Blayney DW, Brooks JD, Hernandez-Boussard T. Seneviratne MG, et al. EGEMS (Wash DC). 2018 Jun 1;6(1):13. doi: 10.5334/egems.234. EGEMS (Wash DC). 2018. PMID: 30094285 Free PMC article.

4

Predicting the Incidence of Pressure Ulcers in the Intensive Care Unit Using Machine Learning.

Cramer EM, Seneviratne MG, Sharifi H, Ozturk A, Hernandez-Boussard T. Cramer EM, et al. Among authors: seneviratne mg. EGEMS (Wash DC). 2019 Sep 5;7(1):49. doi: 10.5334/egems.307. EGEMS (Wash DC). 2019. PMID: 31534981 Free PMC article.

5

User-centred design for machine learning in health care: a case study from care management.

Seneviratne MG, Li RC, Schreier M, Lopez-Martinez D, Patel BS, Yakubovich A, Kemp JB, Loreaux E, Gamble P, El-Khoury K, Vardoulakis L, Wong D, Desai J, Chen JH, Morse KE, Downing NL, Finger LT, Chen MJ, Shah N. Seneviratne MG, et al. BMJ Health Care Inform. 2022 Oct;29(1):e100656. doi: 10.1136/bmjhci-2022-100656. BMJ Health Care Inform. 2022. PMID: 36220304 Free PMC article.

6

Distribution of global health measures from routinely collected PROMIS surveys in patients with breast cancer or prostate cancer.

Seneviratne MG, Bozkurt S, Patel MI, Seto T, Brooks JD, Blayney DW, Kurian AW, Hernandez-Boussard T. Seneviratne MG, et al. Cancer. 2019 Mar 15;125(6):943-951. doi: 10.1002/cncr.31895. Epub 2018 Dec 4. Cancer. 2019. PMID: 30512191 Free PMC article.

7

Expanding the Secondary Use of Prostate Cancer Real World Data: Automated Classifiers for Clinical and Pathological Stage.

Bozkurt S, Magnani CJ, Seneviratne MG, Brooks JD, Hernandez-Boussard T. Bozkurt S, et al. Among authors: seneviratne mg. Front Digit Health. 2022 Jun 2;4:793316. doi: 10.3389/fdgth.2022.793316. eCollection 2022. Front Digit Health. 2022. PMID: 35721793 Free PMC article.

8

Advances in Electronic Phenotyping: From Rule-Based Definitions to Machine Learning Models.

Banda JM, Seneviratne M, Hernandez-Boussard T, Shah NH. Banda JM, et al. Annu Rev Biomed Data Sci. 2018 Jul;1:53-68. doi: 10.1146/annurev-biodatasci-080917-013315. Epub 2018 May 23. Annu Rev Biomed Data Sci. 2018. PMID: 31218278 Free PMC article.

9

Identifying Cases of Metastatic Prostate Cancer Using Machine Learning on Electronic Health Records.

Seneviratne MG, Banda JM, Brooks JD, Shah NH, Hernandez-Boussard TM. Seneviratne MG, et al. AMIA Annu Symp Proc. 2018 Dec 5;2018:1498-1504. eCollection 2018. AMIA Annu Symp Proc. 2018. PMID: 30815195 Free PMC article.

10

Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records.

Tomašev N, Harris N, Baur S, Mottram A, Glorot X, Rae JW, Zielinski M, Askham H, Saraiva A, Magliulo V, Meyer C, Ravuri S, Protsyuk I, Connell A, Hughes CO, Karthikesalingam A, Cornebise J, Montgomery H, Rees G, Laing C, Baker CR, Osborne TF, Reeves R, Hassabis D, King D, Suleyman M, Back T, Nielson C, Seneviratne MG, Ledsam JR, Mohamed S. Tomašev N, et al. Among authors: seneviratne mg. Nat Protoc. 2021 Jun;16(6):2765-2787. doi: 10.1038/s41596-021-00513-5. Epub 2021 May 5. Nat Protoc. 2021. PMID: 33953393

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