Accountable Deep-Learning-Based Vision Systems for Preterm Infant Monitoring

被引：2

作者：

Migliorelli, Lucia ^{[1
]}

Tiribelli, Simona ^{[2
]}

Cacciatore, Alessandro ^{[3
]}

Giovanola, Benedetta ^{[2
,7
]}

Frontoni, Emanuele ^{[4
]}

Moccia, Sara ^{[5
,6
]}

机构：

[1] Univ Politecn Marche, Dept Informat Engn, I-60121 Ancona, Italy

[2] Univ Macerata, Eth, I-62100 Macerata, Italy

[3] Univ Macerata, Dept Humanities, I-62100 Macerata, Italy

[4] Univ Macerata, Comp Sci, Macerata, Italy

[5] BioRobot Inst, Bioengn, I-56127 Pisa, Italy

[6] Dept Excellence Robot & Scuola Super St Anna, I-56127 Pisa, Italy

[7] Tufts Univ, Medford, MA USA

来源：

COMPUTER | 2023年 / 56卷 / 05期

关键词：

Ethics; Pediatrics; Machine vision; Monitoring; CEREBRAL-PALSY;

D O I：

10.1109/MC.2023.3235987

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

This work proposes an ethical framework that highlights possible ethical risks in the design and use of deep-learning-based vision systems for monitoring infants' movements in neonatal intensive care units. We discuss biases and ways to mitigate them for promoting accountable systems in clinical practice.

引用

页码：84 / 93

页数：10

共 50 条

[21] Metamorphic Testing for the Validation of Deep-learning-based Object Detection Systems
Kufer, Dominik, 2025, 127 (01) : 36 - 39
[22] A dataset of the quality of soybean harvested by mechanization for deep-learning-based monitoring and analysis
Chen, Man
Jin, Chengqian
Ni, Youliang
Yang, Tengxiang
Xu, Jinshan
DATA IN BRIEF, 2024, 52
[23] A Deep-learning-based approach to VM behavior Identification in Cloud Systems
Stefanini, Matteo
Lancellotti, Riccardo
Baraldi, Lorenzo
Calderara, Simone
CLOSER: PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND SERVICES SCIENCE, 2019, : 308 - 315
[24] Deep-learning-based ghost imaging
Lyu, Meng
Wang, Wei
Wang, Hao
Wang, Haichao
Li, Guowei
Chen, Ni
Situ, Guohai
SCIENTIFIC REPORTS, 2017, 7
[25] DFUCare Deep-Learning-Based Mobile App for Diabetic Foot Ulcer Monitoring
Sendilraj, Varun
Pilcher, William C.
Bhasin, Manoj K.
DIABETES, 2022, 71
[26] Deep-learning-based multistate monitoring method of belt conveyor turning section
Zhang, Mengchao
Jiang, Kai
Zhao, Shuai
Hao, Nini
Zhang, Yuan
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, 2024, 23 (04): : 2026 - 2039
[27] CropDeep: The Crop Vision Dataset for Deep-Learning-Based Classification and Detection in Precision Agriculture
Zheng, Yang-Yang
Kong, Jian-Lei
Jin, Xue-Bo
Wang, Xiao-Yi
Su, Ting-Li
Zuo, Min
SENSORS, 2019, 19 (05)
[28] Deep-learning-based binary hologram
Goi, Hiroaki
Komuro, Koshi
Nomura, Takanori
APPLIED OPTICS, 2020, 59 (23) : 7103 - 7108
[29] RETRACTION: Mimicking human vision systems: deep-learning-based feature fusion for semantic image retrieval (Retraction of February, 2023)
Chen, Zhongzhe
Zhang, Luming
JOURNAL OF ELECTRONIC IMAGING, 2023, 32 (06)
[30] Deep-Learning-Based Defect Detection for Light Aircraft With Unmanned Aircraft Systems
Connolly, Luke
Garland, James
O'Gorman, Diarmuid
Tobin, Edmond F.
IEEE ACCESS, 2024, 12 : 83876 - 83886

← 1 2 3 4 5 →