BCH AI and Machine Learning Working Group Lightning Talks

Date: September 9, 2020 - 10:30AM

The BCH AI and Machine Learning Working Group held our first Lightning Talks session, where multiple investigators gave brief overviews of numerous Machine Learning applications at Boston Children’s Hospital to foster clinical and machine learning collaborations across the hospital.

Speakers included:

  • John N. Kheir, MD, Department of Cardiology, and Mauricio Santillana, PhD, Computational Health Informatics Program: Predicting unnecessary blood testing for serum potassium in the CICU
  • Maimuna Majumder, PhD, Computational Health Informatics Program: Machine learning applications during COVID-19
  • Rudolph Pienaar, PhD, Department of Radiology: The practical reality of using AI in medical compute
  • Jess Zhang, MPH, and Guarav Tuli, PhD, Innovation Program: Using machine learning to predict food allergy risk
  • Guergana Savova, PhD, Computational Health Informatics Program: How NLP can contribute to various areas of biomedicine — translational science, disease surveillance, clinical decision making, point of care, etc.
  • Timothy Miller, PhD, Computational Health Informatics Program: Extracting useful information from clinical text with NLP
  • Amir Kimia, MD, Clinical Informatics Fellowship, Division of Emergency Medicine: A taste of NLP: Clinical domain experts — helping us to help them
  • Ata Kiapour, PhD, Orthopedic Center: Deep learning for tracking tissue healing following knee surgery
  • Ben Reis, PhD, Computational Health Informatics Program: Predicting the Future in Clinical Settings
  • Yangming Ou, PhD, Department of Radiology: AI+ Imaging to Advance Medicine
  • Mauricio Santillana, PhD, Computational Health Informatics Program: Machine learning to monitor and forecast epidemic outbreaks and patient outcomes in intensive care units
  • Alireza Akhondi-Asl, PhD, Perioperative & Critical Care Center for Outcomes Research and Evaluation: Estimation of state of cerebral autoregulation using a deep long short-term memory (LSTM) network
  • Hsin-Hsao Scott Wang, MD, MPH, MBAn, Urodynamics Program: A new analytical method to solve challenging and critical clinical studies

Publications

Zhang A, Teng L, Alterovitz G. An explainable machine learning platform for pyrazinamide resistance prediction and genetic feature identification of Mycobacterium tuberculosis. Journal of the American Medical Informatics Association : JAMIA 2020.

Geva A, Stedman JP, Manzi SF, Lin C, Savova GK, Avillach P, Mandl KD. Adverse drug event presentation and tracking (ADEPT): semiautomated, high throughput pharmacovigilance using real-world data. JAMIA open 2020.

Börcsök J, Sztupinszki Z, Bekele R, Gao SP, Diossy M, Samant AS, Dillon KM, Tisza V, Spisák S, Rusz O, Csabai I, Pappot H, Frazier ZJ, Konieczkowski DJ, Liu D, Vasani N, Rodrigues JA, Solit DB, Hoffman-Censits JH, Plimack ER, Rosenberg JE, Lazaro JB, Taplin ME, Iyer G, Brunak S, Lozsa R, Van Allen EM, Szüts D, Mouw KW, Szallasi Z. Identification of a synthetic lethal relationship between nucleotide excision repair (NER) deficiency and irofulven sensitivity in urothelial cancer. Clinical cancer research : an official journal of the American Association for Cancer Research 2020.

Gokuldass A, Draghi A, Papp K, Borch TH, Nielsen M, Westergaard MCW, Andersen R, Schina A, Bol KF, Chamberlain CA, Presti M, Met Ö, Harbst K, Lauss M, Soraggi S, Csabai I, Szállási Z, Jönsson G, Svane IM, Donia M. Qualitative Analysis of Tumor-Infiltrating Lymphocytes across Human Tumor Types Reveals a Higher Proportion of Bystander CD8 T Cells in Non-Melanoma Cancers Compared to Melanoma. Cancers 2020.

Perera G, Rijnbeek PR, Alexander M, Ansell D, Avillach P, Duarte-Salles T, Gordon MF, Lapi F, Mayer MA, Pasqua A, Pedersen L, van Der Lei J, Visser PJ, Stewart R. Vascular and metabolic risk factor differences prior to dementia diagnosis: a multidatabase case-control study using European electronic health records. BMJ open 2020.