Hypothesis generation is an early and critical step in any hypothesis-driven clinical research project. However, the process of hypothesis generation is less understood.
In this talk, Dr. Jing will briefly introduce the VIADS (a Visual Interactive Analytic tool for filtering and summarizing large health Data Sets coded with hierarchical terminologies) project and its results* in the last decade. The focus will be on a study that recruited clinical researchers who used (or did not use) VIADS for data-driven hypothesis generation in the clinical research context. The talk will summarize the experiments and principal findings and share the lessons learned. The role of humans and/or AI in the process and challenges in measuring the processes and results will also be discussed.
* Selected publications— PMID: 39819516, 40768504, 40417518, 39211055, 37011112, 38384898, 35736798, 30764811, 24727931, 22195119