Computerized Central Blood Bank Management System (CCBBMS)

Author(s):  
Mohammed Y. Esmail ◽  
Yousra Sayed Hammad Osman
Author(s):  
P.A.J. Sandaruwan ◽  
U.D.L. Dolapihilla ◽  
D.W.N.R. Karunathilaka ◽  
W.A.D.T.L. Wijayaweera ◽  
W.H. Rankothge ◽  
...  

2015 ◽  
Vol 195 ◽  
pp. 2008-2013 ◽  
Author(s):  
Sumazly Sulaiman ◽  
Abdul Aziz K. Abdul Hamid ◽  
Nurul Ain Najihah Yusri

Author(s):  
Aryan Ringshia

Abstract: Blood donation is a vital component of international healthcare and has suffered because of the pandemic. This paper aims to address this issue by proposing the creation of a totally transparent blood bank management system in which hospitals/NGOs input the quantity of each blood type in their stock, after which nearby users who are ready to donate are notified. Following extensive research, we observed that there is no structure in place that provides a communication link between the management of blood banks (Hospitals and NGOs) and the general public, allowing available donors to view which blood banks have a shortage of their blood group. The technology platform in implementing this system uses Python programming environment Django for SQL and deployment. For frontend development, HTML5, CSS3, JavaScript, and Bootstrap were utilized. The system alleviates the issues created by blood shortages in blood banks by properly managing and providing a single platform for everyone. It makes information about available stock in each blood bank available to the public and this can be extended to multiple cities. Keywords: Blood donation, Blood stock, Hospital, Donor, System


Author(s):  
I. Jeena Jacob ◽  
P. Ebby Darney

A blood bank is the organisation responsible for storing blood to transfuse it to the patients in need. The primary goal of a blood bank is to be reliable and ensure that patients get the relevant non-toxic blood to avoid transfusion-related complications since blood is a critical medicinal resource. It is difficult for the blood banks to offer high levels of precision, dependability, and automation in the blood storage and transfusion process if blood bank administration includes many human processes. This research framework is proposing to maintain blood bank records using CNN model classification method. In the pre-processing of CNN method, the datasets are tokenized and set the donor’s eligibility. It will make it easier for regular blood donors to donate regularly to charitable people and organizations. A few machine learning techniques offer the automated website updation. Jupyter note book has been used to analyze the dataset of blood donors using decision trees, neural networks, and von Bays techniques. The proposed method operates online through a website. Moreover, the donor's eligibility status with gender, body mass index, blood pressure level, and frequency of blood donations is also maintained. Finally, the comparison of different machine learning algorithms with the suggested framework is tabulated.


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