Nirmala P

Publications

• Research Article   
  Multivariate Analysis of Nutritional Variables and Inflammatory Biomarkers Using AI Models for Clinical Cancer Risk Prediction
  Author(s): Nirmala P, Priyanka C, Sergey Gupalo, Jegathambigai RN, Kyaw Zaw Win, Thidar Aung, Phone Myint Htoo, Wana Hla Shwe, Aye Aye Tun, Rohini Karunakaran, Manglesh Waran Udayah, Lwin Lwin Nyein, Nang Khin Mya, Thida Khin, Myat Myo Naing, Sutha Devaraj and Nazmul MHM*
  
  The study showcases the application of complex machine learning models that study inflammation and nutrition together for high accuracy early cancer risk prediction. With the help of statistical preprocessing and feature nonlinearity, together with other machine learning models, the system managed to capture the interactions between nutrition and inflammation to a level that other models would not. These models report a validation error that significantly exceeds that of models that only capture the linear components of the relationships involved. Traditional models have been demonstrated to have wide margins of error with regard to the cancer risk predicted. The developed system is smart enough to combine the inflamed glycemic load, saturated fat content, CRP, IL-6, and TNF-α levels, together with antioxidant and omega-3 intake, and model cancer risk. The study describes the bu.. Read More»
  

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