BEGIN:VCALENDAR VERSION:2.0 PRODID:-//132.216.98.100//NONSGML kigkonsult.se iCalcreator 2.20.4// BEGIN:VEVENT UID:20260909T092441EDT-4934WVSAPd@132.216.98.100 DTSTAMP:20260909T132441Z DESCRIPTION:Hi all\, Join us for a talk on core topic\, a journal club\, an d a case study in health IT:  \n\nvia Teams : 2023-2024 link  \n\n9am: Dev eloping an emergency department crowding dashboard: A design science appro ach By: Dr. Saleh Alsaeed\, health informatics emergency medicine fellow\n \nLearning objectives: \n\n1. What is the method for constructing a dashbo ard that gathers real-time information about\n Emergency Department crowdin g?\n 2. How can the dashboard be designed and organized based on functional and non-functional requirements?\n\n​Question: What are the crowding indi cators that need to be measured and displayed on the dashboard?\n\n \n\n 1 0 am – Enabling Precision Dialysis Using IVC Collapsibility AI-Driven Wear able Ultrasonography By: Mohamed Elahmedi\, MBBS PMP MSc(c)\n\nLearning Ob jectives:\n\n\n \n At the end of this presentation\, attendees will recogniz e the value of autonomous IVC collapsibility assessment in emergency and e lective settings.\n \n\n\n\n \n Attendees will have learned of the role of IV C collapsibility assessment in volume depletion and overload\, acute and c hronic.\n \n\n\nQuestion: How reliable is IVC collapsibility assessment in emergency settings? What are the potential indications for IVC collapsibil ity assessment?\n\n \n\n11 am – Research Proposal: Development and Impleme ntation of Personalized Waiting Time Prediction Tool for Emergency Departm ent (ED) Rooms\, By: Hossein Naseri PhD\n\nLearning Objectives:\n\n\n \n How natural language processing (NLP) can aid in extracting pain information from radiography images of patients with bone metastases.\n \n \n How to inte grate NLP and radiomics for predicting pain using radiography images of pa tients with bone metastases.\n \n\n\n\n \n Potential solutions for personaliz ed waiting time estimation.\n \n\n\nQuestion: How can advanced technologies like natural language processing (NLP) be harnessed to improve the analys is of radiography images for patients with bone metastases\, particularly in the context of pain prediction? What potential benefits or challenges d o you foresee in implementing a personalized waiting time prediction tool in Emergency Department (ED) rooms\, and how might the integration of tech nology play a role in addressing these factors?\n\n \n\nBIO: Dr. Saleh Als aeed\, health informatics emergency medicine fellow\, department of emerge ncy medicine\, McGill University. He is from pediatric background\, finish ed his pediatric medicine board back home in Saudi Arabia\, and pediatric emergency medicine fellowship in McMaster prior to be enrolled in his curr ent fellowship. Dr. Saleh has an interest in workflow and human behavior\n \nBIO: Hossein Naseri is a Medical Physics Ph.D. graduate from McGill Univ ersity under the supervision of Dr. John Kildea. Hossein's doctoral resear ch focused on using natural language processing and radiomics to predict p ain in radiography images of patients with bone metastases. Today\, Hossei n proposes a pilot study\, the development and implementation of a persona lized patient waiting time prediction tool for emergency department (ED) r ooms.\n\nBIO: Dr. Mohamed Elahmedi is a general practitioner and an experi enced clinical research project manager with a master’s degree in digital health innovation from McGill University. Having received surgical and fam ily medicine training\, Dr. Elahmedi conducted clinical investigation stud ies on endoscopic bariatric therapy devices. His interdisciplinary knowled ge and experience align him with clinical research\, ethics principles\, m edical technology and AI in Medicine project management. Dr. Elahmedi stro ngly believes that AI is the key to providing precise\, personalized healt hcare.\n DTSTART:20240201T140000Z DTEND:20240201T170000Z SUMMARY:EMHI Rounds URL:https://www.mcgill.ca/emergency/channels/event/emhi-rounds-355068 END:VEVENT END:VCALENDAR