Abstract:
Traditional patient history-taking, often hindered by its time-consuming nature, in-
completeness, and vulnerability to subjective bias, hampers accurate diagnoses and
personalized care. This paper explores the limitations of the current paradigm and
proposes novel approaches with the potential to provide a detailed understanding of
a patient’s health profile, enabling more informed medical decisions and improved
healthcare delivery. Building upon the foundations of Computerized History Taking
(CHT), our work proposed an Automated Patient History-taking framework to ad-
dress these limitations. This framework utilizes an interactive chat system and struc-
tured questioning to gather comprehensive data, minimizing errors and omissions.
Data analysis uncovers hidden patterns, enabling early disease detection, personal-
ized treatments and enhanced accessibility.
Description:
Supervised by
Mr. Shohel Ahmed,
Assistant Professor,
Department of Computer Science and Engineering (CSE)
Islamic University of Technology (IUT)
Board Bazar, Gazipur, Bangladesh
This thesis is submitted in partial fulfillment of the requirement for the degree of Bachelor of Science in Software Engineering, 2024
