International Journal of Research in Signal Processing, Computing & Communication System Design

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RNH Hospital Application and Data Analysis


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1 Shri Ramdeobaba College of Engineering and Management, University of Nagpur Nagpur, Maharashtra, India
     

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This application incorporates various factors needed for smooth working and management of RNH hospital. This hospital application allows administrator to store and manage various resources according to patients’ and doctor’s requirements. The application is developed to eliminate human efforts in managing hospital records and data manually. The system also stores the doctor’s data in a well defined manner. The doctor’s details include his name, number, experience, consultant type specialty and current doctor’s status. This app also provides the information offered by the hospital and details about health packages, data analysis and billing generation. User can also request an appointment as per his/her requirements and ask queries. This application uses the data which is collected from RNH Hospital to perform analysis: on medicines which compares Medicines (on the basis of types of Medicines); set values (Above & Below), on Hospital Growth which compares and computes average (Number of Registrations & Surgeries), on Treatments; comparing them (on the basis of Male & Females, Age Groups) by applying statistical and inferential analysis like Mean, Median, Standard deviation, T-test and Analysis of Variance (ANOVA). The application uses Android Studio as a front end, SQL Server to store it’s back end data and Morris.js using Hypertext Preprocessor (PHP) and Java Script Object Notation (JSON) to perform data analysis. The back end data includes accommodation details and related doctor’s data for effectively managing a hospital. The analyzed data is in graphical format which includes bar graph, pie-chart.

Keywords

ANOVA, Application, Data Analysis, JSON, PHP, T-Test.
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  • A. Luschi, A. Belardinelli, L. Marzi, F. Frosini, R. Miniati, and E. Iadanza, “Careggi smart hospital: A mobile app for patients, citizens and healthcare staff,” 2014 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI 2014), pp. 125-128, 2014.

  • A. Imteaj, and M. K. Hossain, “A smartphone based application to improve the health care system of Bangladesh,” 2016 International Conference on Medical Engineering, Health Informatics and Technology (MediTec), pp. 1-6, 2016.

  • Y. S. Mey, and S. Sankaranarayanan, “Near field communication based patient appointment,” 2013 International Conference on Cloud & Ubiquitous Computing & Emerging Technologies, pp. 98-103, 2013.

  • A. Bharathi, and A. M. Natarajan, “Cancer classification of bioinformatics data using ANOVA,” International Journal of Computer Theory & Engineerig, vol. 2, no. 3, pp. 369-373, 2010.

  • A. Danila, D. Ungureanu, S. A. Moraru, and N. Voicescu, “An implementation of the variance analysis (ANOVA) for the power factor optimization at distribution level in smart grid,” Proc. - 2017 International Conference on Optimization of Electrical and Electronic Equipment (OPTIM) & 2017 Intl Aegean Conference on Electrical Machines and Power Electronics (ACEMP), no. 1, pp. 48-53, 2017.

  • Y. Ukita, T. Matsushima, and S. Hirasawa, “A note on the degrees of freedom in an experimental design model based on an orthonormal system,” 2011 IEEE International Conference on Systems, Man, and Cybernetics, no. 5, pp. 2181-2185, 2011.

  • R. R. Chhikara, and L. Singh, “An improved discrete firefly and t-test based algorithm for blind image steganalysis,” Proc. - International Conference on Intelligent Systems, Modelling and Simulation, ISMS, vol. 2015, pp. 58-63, October 2015.

  • M. Üsame, “T-test feature ranking based 3D MR classification with VBM mask,” vol. l, pp. 1-4, 2017.

  • V. Immler, M. Hiller, J. Obermaier, and G. Sigl, “Take a moment and have some t: Hypothesis testing on raw PUF data,” Proc. 2017 IEEE International Symposium on Hardware Oriented Security and Trust (HOST), pp. 128-129, 2017.

  • D. Iwamoto, K. Honda, and K. Ogawa, “Angle of arrival estimation with improved accuracy using the mean IQ-value method in a rician fading channel,” no. 4, pp. 19-22, 2017.


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  • RNH Hospital Application and Data Analysis

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Authors

Puja Bharti Singh
Shri Ramdeobaba College of Engineering and Management, University of Nagpur Nagpur, Maharashtra, India
Bhakti Khera
Shri Ramdeobaba College of Engineering and Management, University of Nagpur Nagpur, Maharashtra, India
Vipul Bangad
Shri Ramdeobaba College of Engineering and Management, University of Nagpur Nagpur, Maharashtra, India
Purshottam Assudani
Shri Ramdeobaba College of Engineering and Management, University of Nagpur Nagpur, Maharashtra, India

Abstract


This application incorporates various factors needed for smooth working and management of RNH hospital. This hospital application allows administrator to store and manage various resources according to patients’ and doctor’s requirements. The application is developed to eliminate human efforts in managing hospital records and data manually. The system also stores the doctor’s data in a well defined manner. The doctor’s details include his name, number, experience, consultant type specialty and current doctor’s status. This app also provides the information offered by the hospital and details about health packages, data analysis and billing generation. User can also request an appointment as per his/her requirements and ask queries. This application uses the data which is collected from RNH Hospital to perform analysis: on medicines which compares Medicines (on the basis of types of Medicines); set values (Above & Below), on Hospital Growth which compares and computes average (Number of Registrations & Surgeries), on Treatments; comparing them (on the basis of Male & Females, Age Groups) by applying statistical and inferential analysis like Mean, Median, Standard deviation, T-test and Analysis of Variance (ANOVA). The application uses Android Studio as a front end, SQL Server to store it’s back end data and Morris.js using Hypertext Preprocessor (PHP) and Java Script Object Notation (JSON) to perform data analysis. The back end data includes accommodation details and related doctor’s data for effectively managing a hospital. The analyzed data is in graphical format which includes bar graph, pie-chart.

Keywords


ANOVA, Application, Data Analysis, JSON, PHP, T-Test.

References