@article{MAKHILLAJIT20201916782,
    title = {Feasibility and Usability of Facebook Chatbots as a Breast Cancer Risk Assessment Tool},
    journal = {Asian Journal of Information Technology},
    volume = {19},
    number = {1},
    pages = {28-34},
    year = {2020},
    issn = {1682-3915},
    doi = {ajit.2020.28.34},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2020.28.34},
    author = {Bryan Agustine,Elmer and},
    keywords = {cancer,cancer risk assessment,chatbot,Facebook Messenger,supervised machine learning,Breast,web application},
    abstract = {In Asia, the Philippines has the highest
incidence rate of breast cancer. This is one of the most
common forms of cancer which can be detected early and
when treated properly, be cured. There is also no denying
that the Philippines love social media. In fact, the country
is the leader in social media usage amounting to 3 h and
57 min of average use. The purpose of this study is to
take advantage of Facebook’s Messenger platform in
creating a chatbot for breast cancer risk assessment and
assess its feasibility and usability. In order to choose an
accurate model, this study used publicly available data
from the Breast Cancer Surveillance Consortium to
compare the performance of different classification
algorithms. The multilayer perceptron classifier was
chosen as the prediction model since it had the best
performance and was uploaded to a web application. This
web application was then integrated to the Messenger
platform in the form of a chat bot. A convenience sample
of 28 women tested the application and a usability survey
was conducted immediately after. The outcomes are
presented and discussions are made to illustrate the
significance of the results and how it can spearhead
additional or enhance existing public health care services
among assigned government agencies.}
    }