· Second, doctors are having to cope with an ever-expanding workload, which leads to decreased enthusiasm and efficiency.
· Third, qualitative replies are conditioned on doctors’ expertise, experiences and time, which may result in diagnosis conflicts among multiple doctors and low disease coverage of individual doctor.
· It investigates and categorizes the information needs of health seekers in the community-based health services and mines the signatures of their generated data.
· Connected deep learning scheme that is able to infer the possible diseases given the questions of health seekers.
· It permits unsupervised feature learning from other wide range of disease types. Therefore, it is generalizable and scalable.
- Speed - 1.1 Ghz
- Processor - Pentium IV
- RAM - 512 MB (min)
- Hard Disk - 40 GB
- Key Board - Standard Windows Keyboard
- Mouse - Two or Three Button Mouse
- Monitor - LCD/LED
- Operating System : Windows 7
- Front End : ASP.Net and C#
- Database : MSSQL
- Tool : Microsoft Visual studio