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Suggested authors matching "AUTH:Erdman L" with an ORCID

Lauren Erdman
University of Toronto
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Author Correction: The Hydronephrosis Severity Index guides paediatric antenatal hydronephrosis management based on artificial intelligence applied to ultrasound images alone.
Erdman L, Rickard M, Drysdale E, Skreta M, Hua SB, Sheth K, Alvarez D, Velaer KN, Chua ME, Dos Santos J, Keefe D, Rosenblum ND, Bonnett MA, Weaver J, Xiang A, Fan Y, Viteri B, Cooper CS, Tasian GE, [...] Goldenberg A
Sci Rep, 14(1):24475, 18 Oct 2024
Cited by: 0 articles | PMID: 39424912 | PMCID: PMC11489647
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The Hydronephrosis Severity Index guides paediatric antenatal hydronephrosis management based on artificial intelligence applied to ultrasound images alone.
Erdman L, Rickard M, Drysdale E, Skreta M, Hua SB, Sheth K, Alvarez D, Velaer KN, Chua ME, Dos Santos J, Keefe D, Rosenblum ND, Bonnett MA, Weaver J, Xiang A, Fan Y, Viteri B, Cooper CS, Tasian GE, [...] Goldenberg A
Sci Rep, 14(1):22748, 01 Oct 2024
Cited by: 0 articles | PMID: 39349526 | PMCID: PMC11442661
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AI-PEDURO - Artificial intelligence in pediatric urology: Protocol for a living scoping review and online repository.
Khondker A, Kwong JCC, Rickard M, Erdman L, Gabrielson AT, Nguyen DD, Kim JK, Abbas T, Fernandez N, Fischer K, 't Hoen LA, Keefe DT, Nelson CP, Viteri B, Wang HS, Weaver J, Yadav P, Lorenzo AJ
J Pediatr Urol, S1477-5131(24)00523-0, 05 Oct 2024
Cited by: 0 articles | PMID: 39424499
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Artificial Intelligence Tools in Pediatric Urology: A Comprehensive Review of Recent Advances
Chowdhury AT, Salam A, Naznine M, Abdalla D, Erdman L, Chowdhury ME, Abbas TO
Preprints.org, 19 Aug 2024
Cited by: 0 articles | PPR: PPR901448
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Artificial Intelligence Tools in Pediatric Urology: A Comprehensive Review of Recent Advances.
Chowdhury AT, Salam A, Naznine M, Abdalla D, Erdman L, Chowdhury MEH, Abbas TO
Diagnostics (Basel), 14(18):2059, 17 Sep 2024
Cited by: 0 articles | PMID: 39335738 | PMCID: PMC11431426
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Using improvisation to enhance communication skills in 4th year medical students.
Erdman L, Dellasega C
Med Educ, 58(11):1386, 25 Sep 2024
Cited by: 0 articles | PMID: 39318333
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Development of machine learning models predicting mortality using routinely collected observational health data from 0-59 months old children admitted to an intensive care unit in Bangladesh: critical role of biochemistry and haematology data.
Das S, Erdman L, Brals D, Boczek B, Hasan SMT, Massara P, Alam MA, Fahim SM, Mahfuz M, Hoogendoorn M, Zuiderent-Jerak T, Bandsma RHJ, Ahmed T, Voskuijl W
BMJ Paediatr Open, 8(1):e002365, 22 Jul 2024
Cited by: 0 articles | PMID: 39038911 | PMCID: PMC11409392
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Deep-learning computer vision can identify increased nuchal translucency in the first trimester of pregnancy.
Kasera B, Shinar S, Edke P, Pruthi V, Goldenberg A, Erdman L, Van Mieghem T
Prenat Diagn, 44(5):535-543, 01 Apr 2024
Cited by: 0 articles | PMID: 38558081
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Early career investigator biocommentary: Lauren Erdman.
Erdman L
Pediatr Res, 95(7):1670-1671, 23 Apr 2024
Cited by: 0 articles | PMID: 38654094 | PMCID: PMC11245381
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Using Deep Learning to Automate Eosinophil Counting in Pediatric Ulcerative Colitis Histopathological Images
Reigle J, Lopez-Nunez O, Drysdale E, Abuquteish D, Liu X, Putra J, Erdman L, Griffiths AM, Prasath S, Siddiqui I, Dhaliwal J
medRxiv, 05 Apr 2024
Cited by: 0 articles | PPR: PPR833062
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Peer feedback: A tool to improve PA, NP, and physician collaboration and clinical practice.
Gallant A, Erdman L, McBeth L, Ngov LK, Misky G
JAAPA, 37(3):1-4, 01 Mar 2024
Cited by: 0 articles | PMID: 38349079
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Application of STREAM-URO and APPRAISE-AI reporting standards for artificial intelligence studies in pediatric urology: A case example with pediatric hydronephrosis.
Khondker A, Kwong JCC, Rickard M, Erdman L, Kim JK, Ahmad I, Weaver J, Fernandez N, Tasian GE, Kulkarni GS, Lorenzo AJ
J Pediatr Urol, 20(3):455-467, 29 Jan 2024
Cited by: 2 articles | PMID: 38331659
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Early prediction of pediatric asthma in the Canadian Healthy Infant Longitudinal Development (CHILD) birth cohort using machine learning.
He P, Moraes TJ, Dai D, Reyna-Vargas ME, Dai R, Mandhane P, Simons E, Azad MB, Hoskinson C, Petersen C, Del Bel KL, Turvey SE, Subbarao P, Goldenberg A, Erdman L
Pediatr Res, 95(7):1818-1825, 11 Jan 2024
Cited by: 0 articles | PMID: 38212387 | PMCID: PMC11245385
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Imported congenital malaria caused by Plasmodium ovale: A case report.
Erdman LK, Boggild AK, Bitnun A
Ther Adv Infect Dis, 11:20499361241229263, 01 Jan 2024
Cited by: 0 articles | PMID: 38312850 | PMCID: PMC10838024
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Systemic lupus erythematosus phenotypes formed from machine learning with a specific focus on cognitive impairment.
Barraclough M, Erdman L, Diaz-Martinez JP, Knight A, Bingham K, Su J, Kakvan M, Grajales CM, Tartaglia MC, Ruttan L, Wither J, Choi MY, Bonilla D, Appenzeller S, Parker B, Goldenberg A, Katz P, Beaton D, Green R, [...] Touma Z
Rheumatology (Oxford), 62(11):3610-3618, 01 Nov 2023
Cited by: 7 articles | PMID: 36394258 | PMCID: PMC10629781
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Trends in Management of Fetuses with Suspected Lower Urinary Tract Obstruction (LUTO): A High-Risk Fetal and Pediatric Center Experience in a Universal-Access-to-Care System.
Richter J, Doktor F, Good H, Erdman L, Kim JK, Santos JD, Brownrigg N, Chua M, Lorenzo AJ, Rickard M, Mieghem TV, Shinar S
Eur J Pediatr Surg, 34(1):91-96, 22 Aug 2023
Cited by: 0 articles | PMID: 37607585
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Dissociable default-mode subnetworks subserve childhood attention and cognitive flexibility: Evidence from deep learning and stereotactic electroencephalography.
Warsi NM, Wong SM, Germann J, Boutet A, Arski ON, Anderson R, Erdman L, Yan H, Suresh H, Gouveia FV, Loh A, Elias GJB, Kerr E, Smith ML, Ochi A, Otsubo H, Sharma R, Jain P, Donner E, [...] Ibrahim GM
Neural Netw, 167:827-837, 23 Jul 2023
Cited by: 0 articles | PMID: 37741065
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Predicting obstruction risk using common ultrasonography parameters in paediatric hydronephrosis with machine learning.
Khondker A, Kwong JCC, Chancy M, D'Souza N, Kim K, Kim JK, Tse LN, Chua M, Yadav P, Erdman L, Weaver J, Lorenzo AJ, Rickard M
BJU Int, 133(1):79-86, 06 Sep 2023
Cited by: 0 articles | PMID: 37594786
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A quantitative analysis of voiding cystourethrogram features confirms the association between high-grade vesicoureteral reflux with male sex, younger age, and hydronephrosis.
Khondker A, Kwong JCC, Yadav P, Chan JYH, Singh A, Erdman L, Keefe DT, Rickard M, Lorenzo AJ
Can Urol Assoc J, 17(8):243-246, 01 Aug 2023
Cited by: 0 articles | PMID: 37581544 | PMCID: PMC10426409
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Commentary to deep learning based automatic quantification of urethral plate characteristics using the plate objective scoring tool (POST).
Bägli DJ, Erdman L
J Pediatr Urol, 19(5):584-585, 06 Jul 2023
Cited by: 0 articles | PMID: 37481427
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Children hospitalized with community-acquired pneumonia complicated by effusion: a single-centre retrospective cohort study.
Alemayheu G, Lee CSJ, Erdman LK, Wong J, Rutherford C, Smieja M, Khan S, Pernica JM
BMC Pediatr, 23(1):181, 19 Apr 2023
Cited by: 2 articles | PMID: 37072740 | PMCID: PMC10113124
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Reply to Bareille et al. Are Viscoelastometric Assays of Old Generation Ready for Disposal? Comment on "Volod et al. Viscoelastic Hemostatic Assays: A Primer on Legacy and New Generation Devices. J. Clin. Med. 2022, 11, 860".
Volod O, Bunch CM, Miller J, Moore EE, Moore HB, Kwaan HC, Patel SS, Wiarda G, Aboukhaled M, Thomas SG, Fulkerson D, Erdman L, Tincher A, Walsh MM
J Clin Med, 12(2):478, 06 Jan 2023
Cited by: 2 articles | PMID: 36675408 | PMCID: PMC9862366
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Deep learning of renal scans in children with antenatal hydronephrosis.
Weaver JK, Logan J, Broms R, Antony M, Rickard M, Erdman L, Edwins R, Pominville R, Hannick J, Woo L, Viteri B, D'Souza N, Viswanath SE, Flask C, Lorenzo A, Fan Y, Tasian GE
J Pediatr Urol, 19(5):514.e1-514.e7, 06 Jan 2023
Cited by: 0 articles | PMID: 36775719
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Automatic Prediction of Paediatric Cardiac Output From Echocardiograms Using Deep Learning Models.
Ufkes S, Zuercher M, Erdman L, Slorach C, Mertens L, Taylor KL
CJC Pediatr Congenit Heart Dis, 2(1):12-19, 09 Nov 2022
Cited by: 0 articles | PMID: 37970100 | PMCID: PMC10642111
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Differential Expression Enrichment Tool (DEET): an interactive atlas of human differential gene expression.
Sokolowski DJ, Ahn J, Erdman L, Hou H, Ellis K, Wang L, Goldenberg A, Wilson MD
NAR Genom Bioinform, 5(1):lqad003, 23 Jan 2023
Cited by: 1 article | PMID: 36694664 | PMCID: PMC9869326
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1-25 of 125 results

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Search life-sciences literature (45,100,050 articles, preprints and more)

Suggested authors matching "AUTH:Erdman L" with an ORCID

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Author Correction: The Hydronephrosis Severity Index guides paediatric antenatal hydronephrosis management based on artificial intelligence applied to ultrasound images alone.

The Hydronephrosis Severity Index guides paediatric antenatal hydronephrosis management based on artificial intelligence applied to ultrasound images alone.

AI-PEDURO - Artificial intelligence in pediatric urology: Protocol for a living scoping review and online repository.

Artificial Intelligence Tools in Pediatric Urology: A Comprehensive Review of Recent Advances

Artificial Intelligence Tools in Pediatric Urology: A Comprehensive Review of Recent Advances.

Using improvisation to enhance communication skills in 4th year medical students.

Development of machine learning models predicting mortality using routinely collected observational health data from 0-59 months old children admitted to an intensive care unit in Bangladesh: critical role of biochemistry and haematology data.

Deep-learning computer vision can identify increased nuchal translucency in the first trimester of pregnancy.

Early career investigator biocommentary: Lauren Erdman.

Using Deep Learning to Automate Eosinophil Counting in Pediatric Ulcerative Colitis Histopathological Images

Peer feedback: A tool to improve PA, NP, and physician collaboration and clinical practice.

Application of STREAM-URO and APPRAISE-AI reporting standards for artificial intelligence studies in pediatric urology: A case example with pediatric hydronephrosis.

Early prediction of pediatric asthma in the Canadian Healthy Infant Longitudinal Development (CHILD) birth cohort using machine learning.

Imported congenital malaria caused by Plasmodium ovale: A case report.

Systemic lupus erythematosus phenotypes formed from machine learning with a specific focus on cognitive impairment.

Trends in Management of Fetuses with Suspected Lower Urinary Tract Obstruction (LUTO): A High-Risk Fetal and Pediatric Center Experience in a Universal-Access-to-Care System.

Dissociable default-mode subnetworks subserve childhood attention and cognitive flexibility: Evidence from deep learning and stereotactic electroencephalography.

Predicting obstruction risk using common ultrasonography parameters in paediatric hydronephrosis with machine learning.

A quantitative analysis of voiding cystourethrogram features confirms the association between high-grade vesicoureteral reflux with male sex, younger age, and hydronephrosis.

Commentary to deep learning based automatic quantification of urethral plate characteristics using the plate objective scoring tool (POST).

Children hospitalized with community-acquired pneumonia complicated by effusion: a single-centre retrospective cohort study.

Reply to Bareille et al. Are Viscoelastometric Assays of Old Generation Ready for Disposal? Comment on "Volod et al. Viscoelastic Hemostatic Assays: A Primer on Legacy and New Generation Devices. J. Clin. Med. 2022, 11, 860".

Deep learning of renal scans in children with antenatal hydronephrosis.

Automatic Prediction of Paediatric Cardiac Output From Echocardiograms Using Deep Learning Models.

Differential Expression Enrichment Tool (DEET): an interactive atlas of human differential gene expression.

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