MLHOps: Machine Learning Health Operations
Machine Learning Health Operations (MLHOps) is the combination of processes for reliable, efficient, usable, and ethical deployment and maintenance of machine learning models in healthcare settings. This paper provides both a survey of work in this area and guidelines for developers and clinicians t...
Saved in:
| Main Authors: | Faiza Khan Khattak, Vallijah Subasri, Amrit Krishnan, Chloe Pou-Prom, Sedef Akinli-Kocak, Elham Dolatabadi, Deval Pandya, Laleh Seyyed-Kalantari, Frank Rudzicz |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10811924/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Hospital at home (virtual wards): developing a logic model and dark logic model
by: Faiza Yahya, et al.
Published: (2025-05-01) -
Wayfinding Strategies for Non-Emergency Services in Australian Hospitals
by: Shiran Geng, et al.
Published: (2024-12-01) -
COVID-19 Vaccination Uptake and Effectiveness for Hospitalized Cases Among Healthcare Workers in Tertiary Hospital
by: María Eugenia Jiménez-Corona, et al.
Published: (2025-01-01) -
Assessment methodology for Lean Practices in healthcare organizations: case study in a Brazilian public hospital
by: Guilherme Tortorella, et al.
Published: (2019-04-01) -
Detection and distribution of multi-drug resistant (MDR) bacterial isolates of clinical and public health significance on hospital fomites and hands of healthcare workers in Mubi General Hospital.
by: Musa Y. Tula * Joel Filgona , Richard Elisha , Terry L. Thomas , Francis O. Iruolaje
Published: (2022-11-01)