#8409. Conversational stories & self organizing maps: Innovations for the scalable study of uncertainty in healthcare communication

September 2026publication date
Proposal available till 30-05-2025
4 total number of authors per manuscript3510 $

The title of the journal is available only for the authors who have already paid for
Journal’s subject area:
Medicine (all);
Education
Health (social science)
Places in the authors’ list:
place 1place 2place 3place 4
FreeFreeFreeFree
1050 $940 $820 $700 $
Contract №8409.1 Contract №8409.2 Contract №8409.3 Contract №8409.4
1 place - free (for sale)
2 place - free (for sale)
3 place - free (for sale)
4 place - free (for sale)

Abstract:
This study examines how natural language processing and unsupervised machine learning methods can reveal underlying types of uncertainty stories in serious illness conversations. The focus lays on what happens when patients, families and clinicians engage one another in conversation. The study uses actual conversations from a large direct-observation study.
Keywords:
unsupervised deep learning; uncertainty; self-organizing map; conversational story; decision-making

Contacts :
0