Efficacy of mammographic artificial intelligence in detecting different histopathological subtypes of breast cancer / (Record no. 83126)

MARC details
000 -LEADER
fixed length control field 03195cam a2200349 a 4500
003 - CONTROL NUMBER IDENTIFIER
control field EG-GiCUC
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250223032847.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 211114s2020 ua dh f m 000 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency EG-GiCUC
Language of cataloging eng
Transcribing agency EG-GiCUC
041 0# - LANGUAGE CODE
Language code of text/sound track or separate title eng
049 ## - LOCAL HOLDINGS (OCLC)
Holding library Deposite
097 ## - Thesis Degree
Thesis Level M.Sc
099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC)
Classification number Cai01.11.31.M.Sc.2020.He.E
100 0# - MAIN ENTRY--PERSONAL NAME
Personal name Hedaya Wasfy Ali Mohamed
245 10 - TITLE STATEMENT
Title Efficacy of mammographic artificial intelligence in detecting different histopathological subtypes of breast cancer /
Statement of responsibility, etc. Hedaya Wasfy Ali Mohamed ; Supervised Mariam Raafat Louis Bouls , Basma Mohamed Alkalaawy , Passant Essam Eldin Ahmed Shibel
246 15 - VARYING FORM OF TITLE
Title proper/short title فاعلية الذكاء الاصطناعى بالتصوير الشعاعى للثدى فى الكشف عن الأنواع النسيجية المختلفة لسرطان الثدى
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Cairo :
Name of publisher, distributor, etc. Hedaya Wasfy Ali Mohamed ,
Date of publication, distribution, etc. 2020
300 ## - PHYSICAL DESCRIPTION
Extent 116 P. :
Other physical details charts , facsimiles ;
Dimensions 25cm
502 ## - DISSERTATION NOTE
Dissertation note Thesis (M.Sc.) - Cairo University - Faculty of Medicine - Department of Radio-Diagnosis
520 ## - SUMMARY, ETC.
Summary, etc. Background:Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives.AI-based algorithms can also increase the efficiency of interpretation workflows by reducing workload and interpretation time Methods: The study was prospectively carried on 123 female patients with 134 pathologically proven malignant breast lesion (between December 2020 to June 2021); the mean age was 53.6 ± SD 12.0 years old.Females coming to breast imaging unit either for screening or with breast complaint, basic sono-mammography was done. Artificial intelligence images were automatically generated by AI software (Lunit INSIGHT for mammography) from mammographic images. Biopsieswere done for suspicious breast lesions.Artificial intelligence results as well as mammography results were correlated to the pathology as the gold reference standard. Results: Artificial intelligence has higher sensitivity than mammography in detecting malignant breast lesions; sensitivity of the two methods (AI and mammography) was 96.6% vs 87.3% and false negative rate 3.4% vs 12.7% respectively. Also AI was more sensitive to detect cancers with suspicious mass 95.2% vs 75%, suspicious calcifications 100% vs 86.5% as well as asymmetry and distortion 100% vs 84.6%.AI has better performance in detecting different histopathological subtype of breast malignancy as DCIS, IDC and ILC than mammography with sensitivity (100%, 96.7%, 96.6%) vs (88.9%, 89%, 82.2%) respectively.While in other rare types of breast malignancy both AI and mammography showed the same sensitivity 80%
530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE
Additional physical form available note Issued also as CD
653 #4 - INDEX TERM--UNCONTROLLED
Uncontrolled term Artificial intelligence
653 #4 - INDEX TERM--UNCONTROLLED
Uncontrolled term Breast cancer
653 #4 - INDEX TERM--UNCONTROLLED
Uncontrolled term Mammography
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Basma Mohamed Alkalaawy ,
Relator term
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Mariam Raafat Louis Bouls ,
Relator term
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Passant Essam Eldin Ahmed Shibel ,
Relator term
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://172.23.153.220/th.pdf">http://172.23.153.220/th.pdf</a>
905 ## - LOCAL DATA ELEMENT E, LDE (RLIN)
Cataloger Nazla
Reviser Revisor
905 ## - LOCAL DATA ELEMENT E, LDE (RLIN)
Cataloger Shimaa
Reviser Cataloger
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Thesis
Holdings
Source of classification or shelving scheme Not for loan Home library Current library Date acquired Full call number Barcode Date last seen Koha item type Copy number
Dewey Decimal Classification   المكتبة المركزبة الجديدة - جامعة القاهرة قاعة الرسائل الجامعية - الدور الاول 11.02.2024 Cai01.11.31.M.Sc.2020.He.E 01010110084730000 22.09.2023 Thesis  
Dewey Decimal Classification   المكتبة المركزبة الجديدة - جامعة القاهرة مخـــزن الرســائل الجـــامعية - البدروم 11.02.2024 Cai01.11.31.M.Sc.2020.He.E 01020110084730000 22.09.2023 CD - Rom 84730.CD
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