Working Group Webinar Library
Webinar Library
Looking for the Unknown Unknowns: Detection of Residual Confounding in RWE Studies
Real world evidence (RWE) offers an opportunity to conduct timely, large, low-cost studies to answer important clinical questions that may not always be feasible to investigate using randomized controlled trials for practical, financial or ethical reasons. However, RWE research also faces several important challenges.
Data-Efficient Language Model Approaches for Assessing Pulmonary Embolism Diagnostic Certainty in Radiology Reports
Pulmonary embolism (PE) presents a significant diagnostic challenge, necessitating clear and precise communication between radiologists and referring physicians to optimize patient outcomes. Variability in the language used to convey diagnostic uncertainty in computed tomographic pulmonary angiography (CTPA) reports can exacerbate ambiguity, potentially leading to inappropriate clinical management and compromised patient care.
Meet the editors at npj Digital Medicine and npj Health Systems
This webinar provides an opportunity to hear from the editors at Nature portfolio journal (npj) Digital Medicine and Health Systems to understand their journals’ scopes specifically with respect to NLP research. Audience will have an opportunity to ask questions. Presenters
Empower Your Worth: Mastering Salary Negotiation for Women
The Women in AMIA Career Advancement Subcommittee would like to invite you to an upcoming webinar, “Empower Your Worth: Mastering Salary Negotiation for Women.” Please join three senior female informatics leaders as they discuss best practices and techniques for salary negotiation, for internal promotions and for securing new opportunities.
Can NLP-Generated Data Be Used in Clinical Research?
Human language is complex and often equivocal. Unsurprisingly, even the most sophisticated natural language processing (NLP) algorithms inevitably make mistakes. The impact of these mistakes on the results of clinical research that uses NLP-generated data as one of the inputs is uncertain. In this talk, Alexander Turchin will discuss a recent study that has demonstrated that real world evidence analyses are resilient to a moderate error rate in NLP-generated data, supporting the use of NLP in clinical research. Presenter