IRJET- Blood Cross Portal: Blood Deferral Donor using Machine Learning

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 05 | May 2019

www.irjet.net

p-ISSN: 2395-0072

Blood Cross Portal: Blood Deferral Donor using Machine Learning Koushik H. D1, K. R. Sumana2, Sunil Kumar N3 Student, Department of MCA, NIE, Mysuru, India Professor, Computer Science Division, NIE College, Karnataka, India 3Mentor, Intrella Technologies, Karnataka, India ---------------------------------------------------------------------***--------------------------------------------------------------------2Assistant

1PG

Abstract - People giving blood might be deliberate non-

and correspondence. Utilizing GPS (Global Positioning System), we discover contributors closer to the area from where the solicitation is created. The blood searcher demands the blood giver accessibility by closer region and required blood bunch by means of SMS to mechanized blood donation center unit. The Global Position System module which is interfaced to microcontroller gets message from individual who requires blood fluid. Controller scans for required data in the information base. In the event that it matches it comes back with OK message and a SMS alert is sent to power part for getting further assistance for the individuals who need blood.

compensated blood benefactors or substitution contributors as vital by an individual from their very own family or network.

WHO prescribes willful non-compensated blood givers over substitution givers because of the level of blood safety from the two gatherings? In spite of the fact that an individual can deliberately choose to give blood, they might be precluded from giving blood because of reasons relating to the benefactors' safety and additionally beneficiary security, which is essentially alluded to as contributor deferral. Deferral might be worldly delay or changeless rejection from giving blood due to being associated or affirmed with having an irresistible sickness, hematological ailment, or whatever other ailment that will either impact the wellbeing of blood or influence contributors' own wellbeing. In this venture, everything about the of blood giver, regardless of whether they are benefactor deferral or not with complete subtleties.

2. Overall Approach In this paper, we developed an application that identifies the deferral blood donors through questionnaires and categorize them according to the duration of the reasons for their postponement and communicate them and encourage them to proactively donate their blood.

Key Words: Blood Donor, Deferral Donors, Blood Donation, Machine Learning, KNN

1. INTRODUCTION Human blood is pitiful, vital and much prominent. Habitually our country requires around 4 crore units of blood. In any case, out of which the accessibility of blood is 40 lakh units of blood. Blood segments are frequently utilized in dangerous circumstances of seriously sick patients. Hemoglobin and organ gift are the main critical commitment that the individual can serve to our country. It isn't destructive for a grown-up individual to give blood. The anatomy of the giver can recover blood inside couple of days. Similarly, the individual can give a portion of his/her organs like kidney, eye, pancreas and so forth. On the off fortunate that the giver is hereditarily coordinated to recipient. There are sanguine fluid gatherings, for example, A, B, AB, and O. The individual with O-bunch blood is the widespread contributor and the singular with AB+ bunch is the all-inclusive recipient. There are different blood donation centers around India none of them offer the extent for a paramount connection among contributor and beneficiary. In our venture we propose another and productive approach to beat such situations.

Cloud based organizations can improve critical in emergency blood movement since they can enable central and speedy access to supplier's data and zone from wherever and for all will and bourn any devices. Since almost everyone passes on a mobile phone with him, it ensures minute region following

Š 2019, IRJET

|

Impact Factor value: 7.211

Fig -1: Block Diagram of Proposed Work Describes the Sequence of Steps in Recognition of Blood Availability.

2.1 Feature Extraction This application is an open portal. So, any user who chooses to use this application has to fill the form, in turn it is used to predict whether donor is an immediate donor or deferral

|

ISO 9001:2008 Certified Journal

|

Page 6984

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 05 | May 2019

www.irjet.net

donor. The features that are considered in determining whether the donor is deferral or not, are mentioned below.

p-ISSN: 2395-0072

Among the three we consider Euclidean distance is the best, considering its time taken to process the data and accuracy compared to other forms. Similarly, at same time we compare test data and train data sets using SVM algorithm.

Here the data are grouped into clusters (Subsets) and gives the output. The donors attribute is broken down into small clusters and they are matched with previous ones. Finally, we use K-Means to determine to deferral donors by picking one of them as centroid and compare them with other deferral donors and eliminate the less effected donor with higher one. This works in iteration process until you can’t find a centroid or left with only two deferral donors.

Here donors are asked about whether they are under medication, immunization are not. Similarly, application asks further about diseases like Malaria, Blood Pressure and Jaundice are considered into account. In case of female candidate, ladies who are undergoing Menstruation cycle, breast reading and pregnancy cycle are considered. Donors who have underwent surgery, underweight [<50kg], hemoglobin count is less are the factors in question.

2.3 Classification of Donors Once the process is done, the people who are eligible or not, to donate blood is classified into two categories: 1. Deferral Donors – These donors are not eligible for immediate donating of blood are called deferral donors. These donors come under any of these attributes mentioned below. Whether it may be one or several, they are deferral.

Table -1: Attributes taken in project

Fig -1: Flow chart of donor

2.2 Data Extraction Once the user or donor completes filling the given form, the data is then compared with old data set and we obtain desired data. This application uses Three main algorithm to process the given sets. The new data set is considered as Test data set and it is compared with training data set (old data set). Firstly, we input these data sets in three forms KNN algorithm i.e. 

|

Impact Factor value: 7.211

Result yes

Immunization

yes

Blood Pressure [less than 90 and more than 180] Jaundice

yes

Malaria

yes

Mensuration

yes

Pregnant

yes

Surgery

yes

Weight [below 50] Hemoglobin Count Breast Feeding

yes

yes

yes yes

Duration After 3 Days After 3 Days After 15 Days

classification Deferral

After 15 Days After 15 Days After 15 Days After 15 Days After 90 Days After 90 Days After 90 Days After 150 Days

Deferral

Deferral Deferral

Deferral Deferral Deferral Deferral Deferral Deferral Deferral

2. Non-Deferral Donors – These donors are eligible for immediate blood donation. These donors satisfy all the standards or norms set in our database (train datasets).

Euclidean distance, Manhattan distance, Chebyshev distance

© 2019, IRJET

Attributes Medication

|

ISO 9001:2008 Certified Journal

|

Page 6985

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 05 | May 2019

www.irjet.net

2.4 Result Analysis

p-ISSN: 2395-0072

3. CONCLUSION With rapid increase in accidents and donating of blood frequently for money without knowing that it causes temporal postponement or permanent exclusion from donating. To bring awareness to people and encourage them to denote blood and to prevent people from donating blood for money, and enhancement of the hospitality industry. This web application provides every details of the blood donor, whether they are donor or not with complete details. With this system, maintain records and classification of donors has never been faster or easier. Thus, Blood Cross Portal: Blood Deferral Donor Using Machine Learning) application proves to be beneficial to donors, hospitals and needy people.

Chart -1: Data Representation in Pie Chart

ACKNOWLEDGEMENT

People Who can Donate after period of 3 months

I have to thank my guide K. R. Sumana for enormous heading and Sunil Kumar N for your tutoring through this undertaking. My real thankfulness to watchmen for their endowments and accomplices for their assistance.

People Who can Donate after 15 days Deferral donors

REFERENCES

People Who can Donate after 3 days

[1] Bravo, M., Kamel, H., Custer, B., Tomasulo, P. “Factors associated with fainting – before, during and after whole blood donation,” Vox Sanguinis (2011) 101, 303– 312.

[2] Eder, Anne F.; Notari IV, Edward P.; and Dodd, Roger Y. “Do reactions after whole blood donation predict syncope on return donation?” TRANSFUSION Volume 52, December 2012.

[3] Erraguntla, M., Gopal, B., Ramachandran, S., Mayer, R. J. 2012, “Inference of Missing ICD9 Codes Using Text Mining and Nearest Neighbor Techniques,” Hawaii International Conference on System Sciences, 2012.

[4] Kamel, Hany; Tomasulo, Peter; Bravo, Marjorie; Wiltbank, Thomas; Cusick, Robin; James, R. C; and Custer, Brian.

“Delayed adverse reactions to blood donation,” TRANSFUSION, Volume 50, 556-565.

[5] Kamel, Hany; Townsend, Mary; Schroeder, Kadi; Bravo, Marjorie; Erraguntla, Madhav; Whitaker, Barbee; Land, Kevin; Tomasulo, Peter. “UNITED STATES DONOR HEMOVIGILANCE SYSTEM: Experience of 3 participating blood centers,” AABB Annual Meeting & CTTXPO 2011, San Diego, CA. [6] KBSI, Environment, Epidemiology, and Etiology Surveillance and Analysis Toolkit Phase II, 2009, W81XWH08-C-0756.

[7]KBSI.2013"DonorHART™System," https://www.donorhemovigilance.org/Default.aspx [8] Tomasulo, Peter; Kamel, Hany; Bravo, Marjorie; James, Robert C.; and Custer, Brian. “Interventions to reduce the vasovagal reaction rate in young whole blood donors,” TRANSFUSION, Volume 51, July 2011.

Donors The overall deferral and non-deferral donor are represented in pie graph.

Chart-2: Donors Fitness representation in Bar Graph From the 1500 data sets taken after algorithm implementation we can say 92.53% are donors fit to donate in k-means and 95.308 in Support vector machine.

© 2019, IRJET

|

Impact Factor value: 7.211

|

ISO 9001:2008 Certified Journal

|

Page 6986