Bernardo C. Bizzo

Dr. Bernardo C. Bizzo

orcid

Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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15 September 2021 in Nature Medicine
Verified
Journal Article
Closed access
PDF file
IDIttai Dayan
Ittai Dayan
HRHolger Roth
Holger Roth
AZAoxiao Zhong
Aoxiao Zhong
AHAhmed Harouni
Ahmed Harouni
AGAmilcare Gentili
Amilcare Gentili
QLQuanzheng Li
Quanzheng Li

1 December 2022 in Radiology
Verified
Journal Article
Closed access
Dania DayeDania Daye
Dania Daye
WWWalter F. Wiggins
Walter F. Wiggins
MLMatthew P. Lungren
Matthew P. Lungren
TATarik Alkasab
Tarik Alkasab
NKNina Kottler
Nina Kottler
CLCurtis P. Langlotz
Curtis P. Langlotz
Successful clinical implementation of artificial intelligence is facilitated by establishing robust organizational structures to ensure appropriate oversight of algorithm implementation, maintenanc... As the role of artificial intelligence (AI) in clinical practice evolves, governance structures oversee the implementation, maintenance, and monitoring of clinical AI algorithms to enhance quality,...

1 September 2019 in Journal of the American College of Radiology
Verified
Journal Article
Closed access
BBBernardo C. Bizzo
Bernardo C. Bizzo
RARenata R. Almeida
Renata R. Almeida
MMMark H. Michalski
Mark H. Michalski
TATarik K. Alkasab
Tarik K. Alkasab

1 July 2018 in American Journal of Roentgenology
Verified
Journal Article
Closed access
RARenata R. Almeida
Renata R. Almeida
GLGrace C. Lo
Grace C. Lo
MPManuel Patino
Manuel Patino
BBBernardo C. Bizzo
Bernardo C. Bizzo
RCRodrigo Canellas
Rodrigo Canellas
DSDushyant V. Sahani
Dushyant V. Sahani
OBJECTIVE. The purpose of this article is to discuss the advances in CT acquisition and image postprocessing as they apply to imaging the pancreas and to conceptualize the role of radiogenomics and machine learning in pancreatic imaging. CONCLUSION. CT is the preferred imaging modality for assessment of pancreatic diseases. Recent advances in CT (dual-energy CT, CT perfusion, CT volumetry, and radiogenomics) and emerging computational algorithms (machine learning) have the potential to further increase the value of CT in pancreatic imaging.

16 January 2020 in Journal of Digital Imaging
Verified
Journal Article
Closed access
PDF file
RGRomane Gauriau
Romane Gauriau
CBChristopher Bridge
Christopher Bridge
LCLina Chen
Lina Chen
FKFelipe Kitamura
Felipe Kitamura
NTNeil A. Tenenholtz
Neil A. Tenenholtz
BBBernardo C. Bizzo
Bernardo C. Bizzo

13 March 2023 in Journal of the American College of Radiology
Verified
Journal Article
Closed access
BBBernardo C. Bizzo
Bernardo C. Bizzo
GDGiridhar Dasegowda
Giridhar Dasegowda
CBChristopher Bridge
Christopher Bridge
BMBenjamin Miller
Benjamin Miller
JHJames M. Hillis
James M. Hillis
KDKeith J. Dreyer
Keith J. Dreyer