Jahan C. Penny-Dimri

Curriculum Vitae

Newtown, VIC 3220 Australia
jcpd.xyz
{jahan.penny-dimri}@monash.edu
jahanpd

Mission Statement

As a clinician-scientist, my career goals are to firstly deliver high-quality healthcare to my local community, and secondly to innovate cutting-edge technology that builds understanding and ultimately improves the health of our ageing population. My current research exists at the intersection of machine learning and improving outcomes in surgery and critical care, aiming to build models with a flexible understanding of risk.

Employment and Academic Positions

2020 - Current
Research Associate
Monash University
Adjunct academic position
2020 - Current
Surgical Registrar
Barwon Health
Rotations in General Surgery, Vascular Surgery, Orthopaedics, Plastic Surgery
2019 - 2020
Surgical Resident
Barwon Health
Rotations in General Surgery and Cardiothoracic Surgery
2018 - 2019
Internship
Ballarat Health
Rotations in General Surgery, General Medicine, Emergency, and Orthopaedics

Education

2023
PhD
Monash Univerity
Development of a novel machine learning approach and web application (cardiac-ml.com) to predict and identify unique risk factors for postoperative outcomes after cardiac surgery.
2017
MBBS (Hons)
Monash Univerity
2013
BSc (Hons)
Adelaide Univerity
Honours research year developing a novel transduction model for testing lentiviral based gene therapy for cystic fibrosis lung disease.
2011
LLB (Hons)
Adelaide Univerity
Honours degree with a thesis in medical law.
2011
Diploma of Instrumental Music
Adelaide Univerity
Cello at the Elder Conservatorium of Music

Courses and Professional Development

2021
Advanced Life Support (ALS) 2
University of Adelaide
2020
Emergency Management of Surgical Trauma
RACS
2020
Australian and New Zealand Surgical Skills Education and Training (ASSET) course
RACS

Research Summary

Areas of Interest
Machine Learning, Dealing with Missing Data, Self-organisation, Cellular Automata.
H-index
14.0

Publications

First author:

Penny-Dimri, J.C. et al. (2023) “Paying attention to cardiac surgical risk: An interpretable machine learning approach using an uncertainty-aware attentive neural network,” PLOS ONE. Edited by G. Tong, 18(8), p. e0289930. doi:10.1371/journal.pone.0289930.

Penny-Dimri, J.C. et al. (2023) “Tree-based survival analysis improves mortality prediction in cardiac surgery,” Frontiers in Cardiovascular Medicine, 10. doi:10.3389/fcvm.2023.1211600.

Penny‐Dimri, J.C. et al. (2022) “Machine learning to predict adverse outcomes after cardiac surgery: A systematic review and meta‐analysis,” Journal of Cardiac Surgery, 37(11), pp. 3838–3845. doi:10.1111/jocs.16842.

Penny-Dimri, J.C., Bergmeir, C. and Smith, J. (2022) “Dealing with missing data using attention and latent space regularization.” arXiv. doi:10.48550/ARXIV.2211.07059.

Penny-Dimri, J.C. et al. (2021) “Machine Learning Algorithms for Predicting and Risk Profiling of Cardiac Surgery-Associated Acute Kidney Injury,” Seminars in Thoracic and Cardiovascular Surgery, 33(3), pp. 735–745. doi:10.1053/j.semtcvs.2020.09.028.

Penny-Dimri, J.C. et al. (2016) “Characterising the Role of Perioperative Erythropoietin for Preventing Acute Kidney Injury after Cardiac Surgery: Systematic Review and Meta-Analysis,” Heart, Lung and Circulation, 25(11), pp. 1067–1076. doi:10.1016/j.hlc.2016.04.016.

Other author:

Fletcher, C.M. et al. (2023) “Platelet Transfusion in Cardiac Surgery: An Entropy-Balanced, Weighted, Multicenter Analysis,” Anesthesia & Analgesia, 138(3), pp. 542–551. doi:10.1213/ane.0000000000006624.

Fletcher, C.M. et al. (2023) “Platelet Transfusion After Cardiac Surgery,” Journal of Cardiothoracic and Vascular Anesthesia, 37(4), pp. 528–538. doi:10.1053/j.jvca.2022.12.009.

Frentiu, A.A. et al. (2023) “The Prognostic Significance of Red Cell Distribution Width in Cardiac Surgery: A Systematic Review and Meta-Analysis,” Journal of Cardiothoracic and Vascular Anesthesia, 37(3), pp. 471–479. doi:10.1053/j.jvca.2022.11.015.

Hinton, J.V. et al. (2023) “Cryoprecipitate Transfusion After Cardiac Surgery,” Heart, Lung and Circulation, 32(3), pp. 414–423. doi:10.1016/j.hlc.2022.11.007.

Hinton, J.V. et al. (2023) “Association of Perioperative Cryoprecipitate Transfusion and Mortality After Cardiac Surgery,” The Annals of Thoracic Surgery, 116(2), pp. 401–411. doi:10.1016/j.athoracsur.2023.02.054.

Sylivris, A. et al. (2023) “Weekend effect in emergency laparotomy: a propensity score‐matched analysis,” ANZ Journal of Surgery, 93(7–8), pp. 1806–1810. doi:10.1111/ans.18595.

Karri, R. et al. (2022) “Machine learning predicts the short-term requirement for invasive ventilation among Australian critically ill COVID-19 patients,” PLOS ONE. Edited by T.A. Rashid, 17(10), p. e0276509. doi:10.1371/journal.pone.0276509.

Khuong, J.N. et al. (2022) “Troponin as a predictor of outcomes in transcatheter aortic valve implantation: systematic review and meta-analysis,” General Thoracic and Cardiovascular Surgery, 71(1), pp. 12–19. doi:10.1007/s11748-022-01888-2.

Liu, Z. et al. (2022) “Elevated Cardiac Troponin to Detect Acute Cellular Rejection After Cardiac Transplantation: A Systematic Review and Meta-Analysis,” Transplant International, 35. doi:10.3389/ti.2022.10362.

Liu, Z. et al. (2022) “Prognostic Significance of Elevated Troponin in Adult Heart Transplant Recipients: A Systematic Review and Meta-Analysis,” Experimental and Clinical Transplantation, 20(7), pp. 633–641. doi:10.6002/ect.2021.0386.

Perry, L.A. et al. (2022) “Perioperative Neutrophil-Lymphocyte Ratio Predicts Mortality After Cardiac Surgery: Systematic Review and Meta-Analysis,” Journal of Cardiothoracic and Vascular Anesthesia, 36(5), pp. 1296–1303. doi:10.1053/j.jvca.2021.07.001.

Raveendran, D. et al. (2022) “The prognostic significance of postoperative hyperbilirubinemia in cardiac surgery: systematic review and meta-analysis,” Journal of Cardiothoracic Surgery, 17(1). doi:10.1186/s13019-022-01870-2.

Wheatley, J. et al. (2022) “The prognostic value of elevated neutrophil–lymphocyte ratio for cardiac surgery‐associated acute kidney injury: A systematic review and meta‐analysis,” Acta Anaesthesiologica Scandinavica, 67(2), pp. 131–141. doi:10.1111/aas.14170.

Karri, R. et al. (2021) “Machine Learning Outperforms Existing Clinical Scoring Tools in the Prediction of Postoperative Atrial Fibrillation During Intensive Care Unit Admission After Cardiac Surgery,” Heart, Lung and Circulation, 30(12), pp. 1929–1937. doi:10.1016/j.hlc.2021.05.101.

Liu, Z. et al. (2021) “Donor Cardiac Troponin for Prognosis of Adverse Outcomes in Cardiac Transplantation Recipients: a Systematic Review and Meta-analysis,” Transplantation Direct, 8(1), p. e1261. doi:10.1097/txd.0000000000001261.

Liu, Z. et al. (2021) “The association of neutrophil–lymphocyte ratio and platelet–lymphocyte ratio with retinal vein occlusion: a systematic review and meta‐analysis,” Acta Ophthalmologica, 100(3). doi:10.1111/aos.14955.

Lynskey, S.J. et al. (2021) “The influence of patient resilience and health status on satisfaction after total hip and knee arthroplasty,” The Surgeon, 19(1), pp. 8–14. doi:10.1016/j.surge.2020.02.007.

Ramson, D.M. et al. (2021) “Duration of post‐operative antibiotic treatment in acute complicated appendicitis: systematic review and meta‐analysis,” ANZ Journal of Surgery, 91(7–8), pp. 1397–1404. doi:10.1111/ans.16615.

Ramson, D.M., Penny‐Dimri, J.C. and Perry, L.A. (2021) “Academic research retreat: a novel approach to maximize the research and publication efforts of medical students and junior doctors,” ANZ Journal of Surgery, 91(6), pp. 1060–1062. doi:10.1111/ans.16898.

Borg Caruana, C. et al. (2020) “Systematic review and meta-analysis of postoperative troponin as a predictor of mortality and major adverse cardiac events after vascular surgery,” Journal of Vascular Surgery, 72(3), pp. 1132-1143.e1. doi:10.1016/j.jvs.2020.03.039.

Jackson, S.M. et al. (2020) “Prognostic Significance of Preoperative Neutrophil-Lymphocyte Ratio in Vascular Surgery: Systematic Review and Meta-Analysis,” Vascular and Endovascular Surgery, 54(8), pp. 697–706. doi:10.1177/1538574420951315.

Liu, Z. et al. (2020) “The Prognostic Value of Elevated Perioperative Neutrophil-Lymphocyte Ratio in Predicting Postoperative Atrial Fibrillation After Cardiac Surgery: A Systematic Review and Meta-Analysis,” Heart, Lung and Circulation, 29(7), pp. 1015–1024. doi:10.1016/j.hlc.2019.11.021.

Aguiar, P. et al. (2018) “COst–Effectiveness and Budget Impact of Lung Cancer Immunotherapy in South America: Strategies to Improve Access,” Immunotherapy, 10(10), pp. 887–897. doi:10.2217/imt-2017-0183.

Aguiar, P.N. et al. (2018) “The effect of PD-L1 testing on the cost-effectiveness and economic impact of immune checkpoint inhibitors for the second-line treatment of NSCLC,” Annals of Oncology, 29(4), p. 1078. doi:10.1093/annonc/mdx478.

Perry, L.A. et al. (2018) “Glial fibrillary acidic protein for the early diagnosis of intracerebral hemorrhage: Systematic review and meta-analysis of diagnostic test accuracy,” International Journal of Stroke, 14(4), pp. 390–399. doi:10.1177/1747493018806167.

Aguiar, P.N. et al. (2017) “Immune checkpoint inhibitors for advanced non-small cell lung cancer: emerging sequencing for new treatment targets,” ESMO Open, 2(3), p. e000200. doi:10.1136/esmoopen-2017-000200.

Aguiar, P.N. et al. (2017) “The effect of PD-L1 testing on the cost-effectiveness and economic impact of immune checkpoint inhibitors for the second-line treatment of NSCLC,” Annals of Oncology, 28(9), pp. 2256–2263. doi:10.1093/annonc/mdx305.

Perry, L.A. et al. (2017) “Topical cystic fibrosis transmembrane conductance regulator gene replacement for cystic fibrosis-related lung disease,” Paediatric Respiratory Reviews, 22, pp. 47–49. doi:10.1016/j.prrv.2016.10.005.

Perry, L.A. et al. (2016) “Topical cystic fibrosis transmembrane conductance regulator gene replacement for cystic fibrosis-related lung disease,” Cochrane Database of Systematic Reviews, 2016(7). doi:10.1002/14651858.cd005599.pub5.

Cmielewski, P. et al. (2014) “Transduction of ferret airway epithelia using a pre-treatment and lentiviral gene vector,” BMC Pulmonary Medicine, 14(1). doi:10.1186/1471-2466-14-183.