mlsanityData to 7 Oct 2026

Midwifery Learning and Forecasting: Predicting Content Demand with User-Generated Logs

arXiv 2107.02480 ↗First posted 6 Jul 2021stat.ML cs.CY cs.LGcited by 6

Not on the map. Why?

Abstract (arXiv)

Every day, 800 women and 6,700 newborns die from complications related to pregnancy or childbirth. A well-trained midwife can prevent most of these maternal and newborn deaths. Data science models together with logs generated by users of online learning applications for midwives can help to improve their learning competencies. The goal is to use these rich behavioral data to push digital learning towards personalized content and to provide an adaptive learning journey. In this work, we evaluate various forecasting methods to determine the interest of future users on the different kind of contents available in the app, broken down by profession and region.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 11 of its 71 references that are in the map. First posted on arXiv 6 Jul 2021.

Builds on

11 of 71 references.

References · 11

  1. 2017DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networkscited by 1,004
  2. 2015MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systemscited by 195
  3. 2019High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processescited by 147
  4. 2020Deep Learning for Time Series Forecasting: Tutorial and Literature Surveycited by 117
  5. 2016Entity Embeddings of Categorical Variablescited by 85
  6. 2019Evaluating time series forecasting models: An empirical study on performance estimation methodscited by 52
  7. 2017Churn Prediction in Mobile Social Games: Towards a Complete Assessment Using Survival Ensemblescited by 11
  8. 2018A Machine-Learning Item Recommendation System for Video Gamescited by 5
  9. 2019Profiling Players with Engagement Predictionscited by 2
  10. 2020A Time Series Approach To Player Churn and Conversion in Videogamescited by 2
  11. 2017Forecasting Player Behavioral Data and Simulating in-Game Eventscited by 1

Built on by

Cited by year

Citing papers per year: 2021: 1; 2022: 2; 2023: 2; 2024: 1.

6 papers.

  1. 2021A Recommendation System to Enhance Midwives' Capacities in Low-Income Countriescited by 5
  2. 2022User Engagement in Mobile Health Applicationscited by 2
  3. 2022Actionable Recourse via GANs for Mobile Healthcited by 1
  4. 2024The Digital Transformation in Health: How AI Can Improve the Performance of Health Systemscited by 1
  5. 2023Synthetic Data Generator for Adaptive Interventions in Global Healthcited by 0
  6. 2023Adaptive Interventions for Global Health: A Case Study of Malariacited by 0