Paper PublishingPredicting Clinical Re-admission Using Discharge Summaries (PCRUDS)
Objective
The main objective of the project is to implement covid-19 possibility of re-admitting due to some symptoms like fever, cold etc. in histogram form.
Abstract
Before
days in hospitals used to prescribe medicines in project format. As the
technology increasing in most of the fields to make the process easy handling
& robust. The hospital clinical notes are digitalized in electronic
medical/health record (EMR) format. This notes which is being very helpful for
analyzing for future predictions. The data is created by combing the covid-19
issues and his/her health issues to predict the re-admission cases through NLP
(Natural language processing) techniques. In this project implemented covid-19
possibility of re-admitting due to some symptoms like fever, cold etc. in
histogram form. Used medical data which consists of free text in unstructured
form and applies natural language processing (NLP) technique and later worked
on structured data to get response from the data through python.
Key words: Bipolar disorder, Random Forest, SVM, Decision Tree, Machine Learning.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
- Processor: I3/Intel
- Processor RAM: 4GB (min)
- Hard Disk: 128 GB
- Key Board: Standard Windows Keyboard
- Mouse: Two or Three Button Mouse
- Monitor: Any
- Operating System: Windows 7+
- Server-side Script: Python 3.6+
- IDE: Jupyter Notebook
- Libraries Used: Pandas, Numpy.
Learning Outcomes
- About Python.
- About Pandas.
- About Numpy.
- About Machine Learning.
- About Artificial Intelligent.
- About how to use the libraries.
- Virtualization.
- About model choosing.
- Project Development Skills:
- Problem analyzing skills.
- Problem solving skills.
- Creativity and imaginary skills.
- Programming skills.
- Deployment.
- Testing skills.
- Debugging skills.
- Project presentation skills.
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Disclaimer - Takeoff Edu Group Projects, are not associated or affiliated with IEEE, in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, and not projects of or by IEEE.
