When is Machine Learning Data Good?: Valuing in Public Health Datafication-Reference-Cited by-同舟云学术

When is Machine Learning Data Good?: Valuing in Public Health Datafication

Published:2022-04-29 Issue: Volume: Page:
ISSN:
Container-title:CHI Conference on Human Factors in Computing Systems
language:
Short-container-title:

Author:

Thakkar Divy¹,Ismail Azra²,Kumar Pratyush³,Hanna Alex⁴,Sambasivan Nithya¹,Kumar Neha²

Affiliation:

1. Google Research, India

2. Georgia Tech, United States

3. Indian Institute of Technology Madras, India

4. Google Research, United States

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3491102.3501868

Reference104 articles.

1. Michael D Abràmoff , Philip T Lavin , Michele Birch , Nilay Shah , and James C Folk . 2018. Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices. NPJ digital medicine 1, 1 ( 2018 ), 1–8. Michael D Abràmoff, Philip T Lavin, Michele Birch, Nilay Shah, and James C Folk. 2018. Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices. NPJ digital medicine 1, 1 (2018), 1–8.

2. Fábio S Aguiar Rodrigo C Torres João VF Pinto Afrânio L Kritski José M Seixas and Fernanda CQ Mello. 2016. Development of two artificial neural network models to support the diagnosis of pulmonary tuberculosis in hospitalized patients in Rio de Janeiro Brazil. Medical & biological engineering & computing 54 11(2016) 1751–1759. Fábio S Aguiar Rodrigo C Torres João VF Pinto Afrânio L Kritski José M Seixas and Fernanda CQ Mello. 2016. Development of two artificial neural network models to support the diagnosis of pulmonary tuberculosis in hospitalized patients in Rio de Janeiro Brazil. Medical & biological engineering & computing 54 11(2016) 1751–1759.

3. Privacy, Security, and Surveillance in the Global South

4. Data care and its politics

5. Agathe Balayn Bogdan Kulynych and Seda Guerses. 2021. Exploring Data Pipelines through the Process Lens: a Reference Model forComputer Vision. arXiv preprint arXiv:2107.01824(2021). Agathe Balayn Bogdan Kulynych and Seda Guerses. 2021. Exploring Data Pipelines through the Process Lens: a Reference Model forComputer Vision. arXiv preprint arXiv:2107.01824(2021).

Cited by 20 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Understanding Contestability on the Margins: Implications for the Design of Algorithmic Decision-making in Public Services;Proceedings of the CHI Conference on Human Factors in Computing Systems;2024-05-11

2. Machine learning for healthcare that matters: Reorienting from technical novelty to equitable impact;PLOS Digital Health;2024-04-15

3. Agreements ‘in the wild’: Standards and alignment in machine learning benchmark dataset construction;Big Data & Society;2024-04-03

4. Data work and practices in healthcare: A scoping review;International Journal of Medical Informatics;2024-04

5. EFL students’ empowerment using servant leadership: a look through the lens of students in Afghanistan;Cogent Education;2024-03-27