A Novel Approach for ABO Blood Group Prediction using Fingerprint through Optimized Convolutional Neural Network

Patil, Vijaykumar; Ingle, D. R.

doi:10.18201/ijisae.2022.268

Cited by 9 publications

(7 citation statements)

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“…This involves protecting patient data so that malicious actors do not have access to it [13]. Health care providers must also take additional steps to ensure that patient data is kept secure from unauthorized access, either by monitoring data at rest and in transit, or by ensuring their compliance with detailed data privacy regulations [14][15][16][17]. This includes encryption, access control, authentication, data privacy regulations, and training personnel on patient data handling.…”

Section: Methodsmentioning

confidence: 99%

A Novel Information Security Framework for Securing Big Data in Healthcare Environment Using Blockchain

Venugopal,

Rajaganapathi,

Birjepatil

et al. 2023

RAiSE-2023

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Section: Methodsmentioning

confidence: 99%

A Novel Information Security Framework for Securing Big Data in Healthcare Environment Using Blockchain

Venugopal,

Rajaganapathi,

Birjepatil

et al. 2023

RAiSE-2023

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“…Professionals who knows a lot about CNN or has knowledge about related stuff can apply this. Individuals cannot relate or would find it hard apply this method in their study (4) .…”

Section: Review Of Literaturementioning

confidence: 99%

Study on Inheritance of Fingerprint Pattern and its Association with ABO Blood Groups at Nagaon, Assam

Devi¹,

Das²,

Das³

2023

IJST

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Objectives :To analyze the inheritance of fingerprints and blood groups and to finally trace (if any) the possible association between the inheritance of fingerprints and blood groups. Methods: A number of 100 students were randomly chosen from the campus of Nagaon College, Autonomous, Nagaon, Assam. A pre-designed form containing the required space for sample collection was made and distributed, explaining the procedure for thumb impression collection and blood groups. After collection, the prints were classified according to Henry's system, where fingerprints are classified into 3 groups-loops, whorls and arches. Findings: It was observed that Arches which is possibly a recessive trait is more prevalent in Blood Group O which is also the recessive blood type. And loops and whorls was more prevalent in blood types A and B which are co-dominant in nature Novelty: Arch patterns might be of a recessive nature, but the dominancy or recessivity of loops and whorls cannot be firmly determined.

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“…This is due to the fact that blood serves as a channel for the movement of many compounds required by the body [3], [4]. The aviator's breathing oxygen (ABO) system can be used to classify blood [5], [6]. This classification is based on changes in blood agglutinogen (antigen) and agglutinin (antibody) [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Human blood group type detection prototype focusing on agglutinin using microcontroller based photodiode

Lubis,

Harefa,

Al-Khowarizmi

et al. 2024

Bulletin EEI

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Blood is a fluid in the body that mainly serves as a medium for transporting various substances in the body. Detection of human blood group types with this microcontroller utilizes dark and light properties. The dark character appears due to agglomeration, while the light nature arises because of no agglomeration, for this to happen, a liquid reagent is needed. Administration of this liquid uses the aviator's breathing oxygen (ABO) system, which consists of reagent a, reagent b, and reagent c and mixing it with blood on the test paper. The number of blood samples in each reagent is based on blood lancet. Furthermore, the sensors used to detect these properties are photodiode and light emitting diode (LED) each of 3 pieces. The Arduino Uno is used to process sensor input while at the same time producing displayed human blood group type on the display screen. The test is carried out involving 12 blood samples and a medical officer. Medical officer are tasked reading directly the results of mixing between reagents and blood samples, after that are compared with the system. The results show that the deviation of the system reading is 0.167 for the sensor reading distance with the sample as far as 0.5 cm.

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A Novel Approach for ABO Blood Group Prediction using Fingerprint through Optimized Convolutional Neural Network

Cited by 9 publications

References 0 publications

A Novel Information Security Framework for Securing Big Data in Healthcare Environment Using Blockchain

A Novel Information Security Framework for Securing Big Data in Healthcare Environment Using Blockchain

Study on Inheritance of Fingerprint Pattern and its Association with ABO Blood Groups at Nagaon, Assam

Human blood group type detection prototype focusing on agglutinin using microcontroller based photodiode

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