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A Deep Residual U-Net Algorithm for Automatic Detection and Quantification of Ascites on Abdominopelvic Computed Tomography Images Acquired in the Emergency Department: Model Development and Validation

A Deep Residual U-Net Algorithm for Automatic Detection and Quantification of Ascites on Abdominopelvic Computed Tomography Images Acquired in the Emergency Department: Model Development and Validation

In contrast to that study, we attempted to develop an AI segmentation algorithm that can perform both detection of ascites as well as the quantification of the volume of ascites at the same time. A segmentation value of zero means no ascites, and segmentation values of the area of ascites can be used to quantify the exact volume of ascites. In addition, we tried to increase the detection accuracy of the AI algorithm.

Hoon Ko, Jimi Huh, Kyung Won Kim, Heewon Chung, Yousun Ko, Jai Keun Kim, Jei Hee Lee, Jinseok Lee

J Med Internet Res 2022;24(1):e34415

Perspectives of Inpatients With Cirrhosis and Caregivers on Using Health Information Technology: Cross-sectional Multicenter Study

Perspectives of Inpatients With Cirrhosis and Caregivers on Using Health Information Technology: Cross-sectional Multicenter Study

Patients with cirrhosis often require expensive inpatient and outpatient care, mainly centered around complications related to hepatic encephalopathy, variceal bleeding, ascites, and medication management [1]. A critical component of optimal care is the education of patients and their caregivers, and communication with the clinical team [2].

Chathur Acharya, Tejasav S Sehrawat, Deborah B McGuire, Jawaid Shaw, Andrew Fagan, Sara McGeorge, Amy Olofson, Melanie B White, Edith Gavis, Patrick S Kamath, Lori Bergstrom, Jasmohan Singh Bajaj

J Med Internet Res 2021;23(4):e24639

A Smartphone App to Manage Cirrhotic Ascites Among Outpatients: Feasibility Study

A Smartphone App to Manage Cirrhotic Ascites Among Outpatients: Feasibility Study

Ascites represents a major burden for patients with cirrhosis. Cirrhotic ascites is associated with poor health-related quality of life [1], hospital admissions [2-4], high cost of care [4-6], and increased mortality [3,7]. For decades, body weight has been identified as a useful proxy for ascites volume, but accurate weight monitoring at home has been difficult. In fact, monitoring weight is central to expert guidelines for ascites management [8,9] and treatment trials [10-12].

Patricia Bloom, Thomas Wang, Madeline Marx, Michelle Tagerman, Bradley Green, Ashwini Arvind, Jasmine Ha, Judith Bloom, James M Richter

JMIR Med Inform 2020;8(9):e17770