Precision in chromosome karyotyping (Record no. 23322)

MARC details
000 -LEADER
fixed length control field a
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250813140952.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250813b xxu||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency AIKTC-KRRC
Transcribing agency AIKTC-KRRC
100 ## - MAIN ENTRY--PERSONAL NAME
9 (RLIN) 27054
Author Velevela, Raghu Ram Chowdary
245 ## - TITLE STATEMENT
Title Precision in chromosome karyotyping
Remainder of title : an automated detection system
250 ## - EDITION STATEMENT
Volume, Issue number Vol.3(3), Sep-Dec
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Ghaziabad
Name of publisher, distributor, etc. MAT Journals
Year 2024
300 ## - PHYSICAL DESCRIPTION
Pagination 20-30p.
520 ## - SUMMARY, ETC.
Summary, etc. In this study, an intelligent system tailored explicitly for the meticulous task of identifying and categorizing chromosomes in the context of karyotyping, a critical process in genetics and medical diagnosis. To achieve this, this project leveraged the capabilities of the YOLO (You Only Look Once) object detection framework, a sophisticated tool widely employed in computer vision. Our methodology involved training the system to recognize and categorize individual chromosomes by exposing them to diverse images containing these genetic structures. Our intelligent system presents several notable advantages. Firstly, it operates remarkably quickly, significantly reducing the time required for chromosome analysis. Secondly, it demonstrates exceptional accuracy, minimizing errors inherent in manual analysis. The implications of this system are profound, offering benefits to clinical geneticists and researchers. Medical professionals can utilize it to understand genetic conditions better, facilitating more precise diagnoses. Simultaneously, researchers can expedite their genetic studies, capitalizing on the efficiency of our automated system. The development process encompassed the creation of an extensive dataset comprising annotated chromosome images, serving as the foundational material for training our YOLO model. We achieved outstanding precision and recall rates through meticulous fine.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
9 (RLIN) 22400
Topical term or geographic name entry element Data Science
700 ## - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 27061
Co-Author Samhitha, V. Veda
773 0# - HOST ITEM ENTRY
Title Journal of innovations in data science and big data management
Place, publisher, and date of publication Ghaziabad MAT Journals
856 ## - ELECTRONIC LOCATION AND ACCESS
URL https://matjournals.net/engineering/index.php/JIDSBDM/article/view/832
Link text Click here
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Articles Abstract Database
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Total Checkouts Barcode Date last seen Price effective from Koha item type
    Dewey Decimal Classification     School of Engineering & Technology School of Engineering & Technology Archieval Section 13/08/2025   2025-1318 13/08/2025 13/08/2025 Articles Abstract Database
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