In this context, our project is devoted to the elaboration of AI-based solution for improving the outcomes of initial cancer diagnostics, based on data types including medical image analysis, genomic data and electronic health records. First, it means helping medical researchers and other health care professionals to accurately predict classes of cancer and recognize high-risk individuals and patients.
With the help of the improved machine learning algorithms, we have designed a system, that is capable to analyze big amount of data and identify cancer. This approach also enhances the alarms and cancer or canker type and stage which is vital in the cancer therapy. The current development relies on research with a extensive selection of databases and the researchers propose to manage the system by gaining much more detailed knowledge of cancerous cells.
In the future, we will predict particular kinds of cancer more precisely at particular stages so that early diagnosis and precise therapy can be implemented. This work thus aims at deploying AI and healthcare so that we can change the current cancer diagnostic approaches and make a huge step in fighting this disease.
Getting a low testing accuracy and higher training accuracy, leading to overfitting of model in which the data isn't trained well on validation data which results in nwrong prediction.
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