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Assessing accuracy and consistency in intracranial aneurysm sizing : human expertise vs. artifcial intelligence
ID Planinc, Andrej (Avtor), ID Špegel, Nina (Avtor), ID Podobnik, Zala (Avtor), ID Šinigoj, Uroš (Avtor), ID Skubic, Petra (Avtor), ID Choi, June Ho (Avtor), ID Park, Wonhyoung (Avtor), ID Robič, Tina (Avtor), ID Tabor, Nika (Avtor), ID Jarabek, Leon (Avtor), ID Špiclin, Žiga (Avtor), ID Bizjak, Žiga (Avtor)

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Izvleček
Intracranial aneurysms (IAs) are a common vascular pathology and are associated with a risk of rupture, which is often fatal. Aneurysm growth of more than 1 mm is considered a surrogate of rupture risk, therefore, this study presents a comprehensive analysis of intracranial aneurysm measurements utilizing a dataset comprising 358 IA from 248 computed tomography angiography (CTA) scans measured by four junior raters and one senior rater. The study explores the variability in sizing assessments by employing both human raters and an Artificial Intelligence (AI) system. Our findings reveal substantial inter- and intra-rater variability among junior raters, contrasting with the lower intra-rater variability observed in the senior rater. Standard deviations of all raters were above the threshold for IA growth (1 mm). Additionally, the study identifies a systemic bias, indicating a tendency for human experts to measure aneurysms smaller than the AI system. Our findings emphasize the challenges in human assessment while also showcasing the capacity of AI technology to improve the precision and reliability of intracranial aneurysm assessments, especially beneficial for junior raters. The potential of AI was particularly evident in the task of monitoring IA at various intervals, where the AI-based approach surpassed junior raters and achieved performance comparable to senior raters.

Jezik:Angleški jezik
Ključne besede:intrarater variability, interrater variability, deep learning, intracranial aneurysms
Vrsta gradiva:Članek v reviji
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:FE - Fakulteta za elektrotehniko
MF - Medicinska fakulteta
Status publikacije:Objavljeno
Različica publikacije:Objavljena publikacija
Založnik:Springer Nature
Leto izida:2024
Št. strani:11 str.
Številčenje:14, art. 16080
PID:20.500.12556/RUL-160094 Povezava se odpre v novem oknu
UDK:004.8:616-007.64
ISSN pri članku:2045-2322
DOI:10.1038/s41598-024-65825-4 Povezava se odpre v novem oknu
COBISS.SI-ID:204579587 Povezava se odpre v novem oknu
Datum objave v RUL:20.08.2024
Število ogledov:220
Število prenosov:43
Metapodatki:XML DC-XML DC-RDF
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Gradivo je del revije

Naslov:Scientific reports
Skrajšan naslov:Sci. rep.
Založnik:Nature Publishing Group
ISSN:2045-2322
COBISS.SI-ID:18727432 Povezava se odpre v novem oknu

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:variabilnost ocenjevalcev, globoko učenje, intrakranialne anevrizme

Projekti

Financer:ARIS - Javna agencija za znanstvenoraziskovalno in inovacijsko dejavnost Republike Slovenije
Številka projekta:J2-3059
Naslov:Sprotno prilagajanje načrta protonske in radioterapije

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