DATA ANALYSIS AND DETECTION OF CONTRADICTION IN BIOMEDICAL LITERATURE
S. Gandhimathi Alias Usha, Aishwarya S S, E. Amrutha, H. Chaithali. · Journal of Critical Reviews · 2020
In every pharma industry, there is a literature inferred with every drug. The drug literature is prepared by medical expert authors and it goes through several review cycle by different experts. The literature is prepared with full of bio medical terms, so it is difficult to interpret and detect contradiction manually and it is time consuming. Hence our main aim of the project is to create a machine learning fledged model which can detect the contradictory statements which can be life threatening as it talks ambiguous and can distort some critical factual information about some medicine or the way of using it. The created model will analyze the documents with the medical terminology known to it. Hence it will make the review process much simpler by optimizing the time complexity reduced from months together to minutes and also avoiding the human errors with high accuracy.