Indian scientists develop Artificial Intelligence in Medicine for prediction of esophageal cancer

Indian scientists develop Artificial Intelligence in Medicine for prediction of esophageal cancer

By Dinesh C Sharma

New Delhi,
July 31 (India Science Wire):  Esophageal
cancer or cancer of the food pipe is among common cancers that occur in
India. Every year some 47,000 new cases are reported and 42,000 people die due
to this cancer. Its occurrence is particularly high in the north-eastern
states. It is often diagnosed late as its symptoms are not very specific and
patients are treated for other causes. In such a situation, early diagnosis can
help save lives.

Researchers
from the Indian Institute of Technology, Kharagpur have used machine
learning techniques
to come up with a possible solution. They have developed
a machine learning-based algorithm for predicting signs of esophageal cancer,
based on demographic data and results of certain clinical tests. This can help
in screening people for further tests to confirm if they indeed have cancer or
not. It is actually a pre-screening tool which can be used by health workers in
rural areas.

The software
has been developed using data of 3000 persons collected by mobile screening
vans of Mumbai-based Tata Memorial Hospital in rural areas of Maharashtra. From
the data collected by paramedical staff on various points, researchers used data
on 49 points such as tobacco consumption, tobacco chewing duration, alcohol
consumption, cancer deaths in family, difficulty in swallowing etc. The cancer
of the food pipe is usually accompanied by symptoms like pain while swallowing
and hoarse voice.

“This
software may be installed in premises of hospitals or health centres or can be
hosted in cloud and accessed over the internet. A suspected patient can enter
his or her demographic information, lifestyle details and available clinical
test results. The software can predict if the patient has a particular
disease. The prediction can be refined by adding more test results. If the
prediction is positive, he or she may contact a doctor for further tests and
treatment,” explained Dr Sourangshu Bhattacharya, assistant professor of
computer science and engineering at IIT Kharagpur, who co-authored the study
along with Ph D student Asis Roy.

The
researchers used open source machine learning software – Weka and LibSVM –
along with python for developing the prediction software. The objective was to
control the parameters of machine learning algorithm so as to make false normal
rate (number of diseased people being marked as normal) zero and selection of
features (tests conducted by medical laboratories) based on criteria of cost or
convenience.

“We searched
through all combinations of 15 tests, costing a total of Rs 6500 and found
subsets of tests costing Rs 2000, which have zero false negative rate. We could
then find the subset which gives the highest accuracy. Similarly, we assigned
indices of discomfort to each of the tests and assigned budgets to total
discomfort that a patient may be willing or be able to suffer in order to get
an initial diagnosis. The main idea was to allow users of the software or
implementing agencies to be able to customize selection of initial tests based
on individual requirements,” explained Dr Bhattacharya while speaking to India
Science Wire
.

Machine learning based algorithm can facilitate in the prediction of esophageal cancer relying on demographic, lifestyle, medical history and customized clinical test, with a very high accuracy up to 99.18% with a sensitivity nearing 100%, researchers have claimed in the study published in journal Artificial Intelligence in Medicine.

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