Machine Learning is an emerging field concerned with the analysis of large and multiple variable data. It involves computationally important methods, algorithms and techniques for analysis. In context of Medical Science, Machine Learning promises to help physicians make near-perfect diagnoses, choose the best medications for their patients, identify patients at high-risk for poor outcomes, and in general improve patients’ health while minimizing costs. This is happening at a rapid pace despite the many hurdles, social acceptance being the major one.
We have Namrata Bilurkar with us, who is currently pursuing her pre-final year of engineering at SJB Institute of Technology, Bangalore. Apart from being a blogger and an open source enthusiast, she is an enthusiast researcher who is trying her hands on Medical Science using Machine Learning techniques !
Let’s know more about her research !
Your Domain of research :
Application of Machine Learning techniques to the field of medical sciences.
What is your research about ? Explain with some analogies and/or examples
- My research is about applying algorithms based on Neural networks to predict the accuracy in diagnosis of Cancer among patients. Since cancer is a fatal disease and as of now there is no known cure to it, the earlier it is diagnosed in a patient the higher will be their rate of life expectancy as it can then be curbed either via medications or operated on, but that is for the doctors to deal with. My research focuses on assisting the doctors make a better diagnosis of higher accuracy rate.
How is your research unique ?
- During my search for a domain of interest I went through several papers on loads of topics but the idea of intermixing computer science and medical sciences is not something which is very common. I find medical sciences fascinating and applying my domain (computer science) to it in order to help improvise the quality of life is what made me pursue my research.
How does your research help the people in industry or in academia ?
- My research involves working on the domain of prediction based on the input data sets. The algorithms used are self-learning and hence based on the data sets provided it can be expanded to other areas and is not restricted strictly to the field of medical sciences alone.
Where did you get the inspiration about the research (A professor who guided you, or maybe you got inspiration from a peer, or a senior. Describe a little) ?
- I came across machine learning multiple times, in articles on different blogs or being mentioned casually by my friends and it got me curious. So, like I do with everything new, I looked it up on Google and came across the Machine Learning course (an MOOC) on Coursera and enrolling onto that course was my starting point. Eventually, I discussed it with my lecturer and together we worked on it.
Any advice for newbies in this field of research ? Any good competitions/conferences the students should apply for ? How to take a start with research ?
- Machine Learning is a branch of Artificial Intelligence, the initial craze about working on something cool like this will eventually fade. I would say if you are working on this field of research then be willing to put in efforts because it demands you to and besides everything else do the research for yourself. Do it because you like the domain and are passionate about it. Not because of any other reasons. There are several National and International conferences, if the work done is substantial then students can apply to those. There are also events like Grace Hopper Celebration which is held every year and if students are interested then they can present their paper at an event like that too.
Any outstanding achievement or recognition for the project/research?
- This research has been published under the title of ‘GRNN and PNN Models for Cancer Prognosis and Prediction’ in the International Journal of Innovative Technology and Research.
Contact details for the people to reach out to you.
We are very sure that Namrata’s research work would have inspired or motivated many of you. We would be constantly unearthing the hidden talents all across the country. To read more of our interviews, visit our research blog series. You can also comment down below, anything that you have to say about the article above. If you want your research work to be covered by The College Store, contact us here. And of course, stay tuned for more
To know more about us, visit About Us.
Team College Store