| dc.description.abstract | Obesity has become an epidemic
condition in Sri Lanka as well as around the
world. It is proven beyond doubt that Bariatric
Surgery (BS) is the most effective option in
treating morbid obesity patients, whose Body
Mass Index (BMI) is greater than 40.0. After
undergoing surgery, it is required to monitor a
patient's weight for eighteen months until they
reach a healthy weight that falls within the
normal BMI range (18.5-24.9). This study has
analysed records of bariatric patients registered
at Colombo South Teaching Hospital, Kalubowila
under three surgery types. Records show that
due to the inability of tracking their weight loss
throughout the post-surgery period and lack of
continuous assessment after BS, majority of
patients have lost their track of weight before
reaching the eighteenth month. Therefore, some
patients have to go through the same operation
more than once, which creates a threat to their
lives. This study aims to remotely track pre-and
post-surgery bariatric patients and allow them to
keep track of their weight loss until they achieve
their expected weight using a web-based weight
prediction system based on artificial neural
networks. To predict the final weight bariatric
patients might get after the surgery, pre-surgery
and post-surgery data are taken as inputs. Mainly
three predictions are aimed to be given as the
outputs; namely pre-surgery, post-surgery and
monthly weight. Machine learning algorithms
like artificial neural networks provide an average
of 85% accuracy in predicting the weight until
the patient achieves the expected result in the
final month. | en_US |
