Lonsdale H - Search Results

1

Artificial Intelligence in Anesthesiology: Hype, Hope, and Hurdles.

Lonsdale H, Jalali A, Gálvez JA, Ahumada LM, Simpao AF. Lonsdale H, et al. Anesth Analg. 2020 May;130(5):1111-1113. doi: 10.1213/ANE.0000000000004751. Anesth Analg. 2020. PMID: 32287116 No abstract available.

2

Quality Initiative Using Theory of Change and Visual Analytics to Improve Controlled Substance Documentation Discrepancies in the Operating Room.

Dolan JE, Lonsdale H, Ahumada LM, Patel A, Samuel J, Jalali A, Peck J, DeRosa JC, Rehman M, Varughese AM, Fernandez AM. Dolan JE, et al. Among authors: lonsdale h. Appl Clin Inform. 2019 May;10(3):543-551. doi: 10.1055/s-0039-1693688. Epub 2019 Jul 31. Appl Clin Inform. 2019. PMID: 31365940 Free PMC article.

3

Machine Learning and Artificial Intelligence in Pediatric Research: Current State, Future Prospects, and Examples in Perioperative and Critical Care.

Lonsdale H, Jalali A, Ahumada L, Matava C. Lonsdale H, et al. J Pediatr. 2020 Jun;221S:S3-S10. doi: 10.1016/j.jpeds.2020.02.039. J Pediatr. 2020. PMID: 32482232 No abstract available.

4

Deep Learning for Improved Risk Prediction in Surgical Outcomes.

Jalali A, Lonsdale H, Do N, Peck J, Gupta M, Kutty S, Ghazarian SR, Jacobs JP, Rehman M, Ahumada LM. Jalali A, et al. Among authors: lonsdale h. Sci Rep. 2020 Jun 9;10(1):9289. doi: 10.1038/s41598-020-62971-3. Sci Rep. 2020. PMID: 32518246 Free PMC article.

5

Machine Learning Applied to Registry Data: Development of a Patient-Specific Prediction Model for Blood Transfusion Requirements During Craniofacial Surgery Using the Pediatric Craniofacial Perioperative Registry Dataset.

Jalali A, Lonsdale H, Zamora LV, Ahumada L, Nguyen ATH, Rehman M, Fackler J, Stricker PA, Fernandez AM; Pediatric Craniofacial Collaborative Group. Jalali A, et al. Among authors: lonsdale h. Anesth Analg. 2021 Jan;132(1):160-171. doi: 10.1213/ANE.0000000000004988. Anesth Analg. 2021. PMID: 32618624

6

The Perioperative Human Digital Twin.

Lonsdale H, Gray GM, Ahumada LM, Yates HM, Varughese A, Rehman MA. Lonsdale H, et al. Anesth Analg. 2022 Apr 1;134(4):885-892. doi: 10.1213/ANE.0000000000005916. Anesth Analg. 2022. PMID: 35299215 No abstract available.

7

A machine-learning approach for decision support and risk stratification of pediatric perioperative patients based on the APRICOT dataset.

Gray GM, Ahumada LM, Rehman MA, Varughese A, Fernandez AM, Fackler J, Yates HM, Habre W, Disma N, Lonsdale H. Gray GM, et al. Among authors: lonsdale h. Paediatr Anaesth. 2023 Sep;33(9):710-719. doi: 10.1111/pan.14694. Epub 2023 May 21. Paediatr Anaesth. 2023. PMID: 37211981

8

Machine Vision and Image Analysis in Anesthesia: Narrative Review and Future Prospects.

Lonsdale H, Gray GM, Ahumada LM, Matava CT. Lonsdale H, et al. Anesth Analg. 2023 Oct 1;137(4):830-840. doi: 10.1213/ANE.0000000000006679. Epub 2023 Sep 5. Anesth Analg. 2023. PMID: 37712476 Review.

9

Pediatric Cannabinoid Hyperemesis: A Single Institution 10-Year Case Series.

Lonsdale H, Kimsey KM, Brown JM, Dey A, Peck J, Son S, Wilsey M. Lonsdale H, et al. J Adolesc Health. 2021 Feb;68(2):255-261. doi: 10.1016/j.jadohealth.2020.09.024. Epub 2020 Oct 27. J Adolesc Health. 2021. PMID: 33127240

10

Paediatric cannabinoid hyperemesis.

Lonsdale H, Wilsey MJ. Lonsdale H, et al. Curr Opin Pediatr. 2022 Oct 1;34(5):510-515. doi: 10.1097/MOP.0000000000001157. Epub 2022 Aug 10. Curr Opin Pediatr. 2022. PMID: 35946907 Review.

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