Diagnostic accuracy of clinical decision support system (CDSSs) ORADIII and ORAD DDX in comparison to histopathological diagnosis of jaw lesions (Record no. 3471)

MARC details
000 -LEADER
fixed length control field 03602nam a22002177a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251007120618.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 251007b |||||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Description conventions NLM
060 ## - NATIONAL LIBRARY OF MEDICINE CALL NUMBER
Classification number WU 270
Item number 00759
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Bali, Harleen Dr.
245 ## - TITLE STATEMENT
Title Diagnostic accuracy of clinical decision support system (CDSSs) ORADIII and ORAD DDX in comparison to histopathological diagnosis of jaw lesions
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Kathmandu, Nepal ;
Name of publisher, distributor, etc. Kathmandu University & Nepal Health Research Council (NHRC) ;
Date of publication, distribution, etc. 2025.
300 ## - PHYSICAL DESCRIPTION
Extent 65p.
500 ## - GENERAL NOTE
General note In partial fulfilment of the requirements for the degree of Master in Medical Research.
520 ## - SUMMARY, ETC.
Summary, etc. Abstract: <br/>Background: With the coming age, integration of Artificial Intelligence is seen in almost all aspects of life, even medical field especially the field of radiology. Clinical Decision Support Systems (CDSSs) like ORADII and ORAD DDx are available to help diagnosis oral intra bony lesion. However, their diagnostic validity remains to be fully established and limitations need to be explored, especially when compared to gold standard of Diagnosis i.e. histopathological diagnosis.<br/><br/>Objectives: To evaluate and compare the diagnostic performance of two CDSS tools- ORADIII and ORAD DDx-against histopathological diagnosis in identifying intra-bony jaw lesions using orthopantomograms (OPGs). <br/><br/>Materials and Method: A cross-sectional diagnostic accuracy study was conducted on a samples comprising both lesion and non-lesion cases based on radiographic evaluation. Diagnostic outputs from ORADIII and ORAD DDx were compared with histopathology. Key performance indicators-including sensitivity, specificity, accuracy, F1 score, Positive Predictive Value (PPV), Negative Predictive Value (NPV), and likelihood ratios (LR+ and LR-)-were calculated for both systems. Concordance, partial concordance, and discordance with histopathological diagnosis were also assessed.<br/><br/>Results: Among the 350 samples evaluated, including 175 lesion-positive and 175 non-lesion cases, ORAD DDx demonstrated superior diagnostic performance compared to ORADIII. The sensitivity, specificity, accuracy, and F1 score for ORADIII were 64.57%, 60.00%, 62.29%, and 0.6314, respectively. In contrast, ORAD DDx achieved sensitivity, specificity, accuracy, and F1 score of 70.29%, 65.71%, 68.57%, and 0.6869 respectively. The positive predictive value (PPV) and negative predictive value (NPV) for ORADIII were 61.75% and 62.87%, while for ORAD DDx, these were 67.21% and 68.86%, respectively. The positive likelihood (LR+) and negative likelihood ratio (LR-) were 1.614 and 0.5905 for ORADIII, compared to 2.050 and 0.4513 for ORAD DDx.<br/><br/>Conclusion: in this study, ORADIII and ORAD DDx demonstrated moderate diagnostic performance when compared to the gold standard of histopathological diagnosis. ORAD DDx showed slightly higher sensitivity, specificity, and diagnostic accuracy than ORADIII, with greater concordance, in identifying intra-bony jaw lesions. However, both systems provide radiographic-level diagnoses and do not replace histopathological evaluation. Their utility lies in supporting clinical decision-making, while they show promise, further refinement and validation are needed before clinical integration as reliable diagnostic tools.<br/><br/>Keywords: artificial intelligence; clinical decision support systems; jaw diseases/diagnosis; diagnostic imaging. <br/>
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Artificial intelligence
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Clinical decision support systems
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Jaw diseases/diagnosis
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Diagnostic imaging
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme National Library of Medicine
Koha item type Thesis Report
Call number prefix THS00759-BAL-2025
Suppress in OPAC No
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Source of acquisition Total Checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
    Dewey Decimal Classification     Nepal Health Research Council Nepal Health Research Council Thesis Cart 10/07/2025 Self Collection   WU 270/THS00759/BAL/2025 THS00759 10/07/2025 1 10/07/2025 Thesis Report

Nepal Health Research Council © 2024.

Ramshah Path, Kathmandu, Nepal, P.O.Box 7626

Web: https://nhrc.gov.np/ | Email : nhrc@nhrc.gov.np | Phone : 977-1-4254220

Maintained by Chandra Bhushan Yadav, Library & Information Officer, NHRC