98 citations · 477 across the 25 of their papers we have counts for
25 papers
Data-Driven Approach to Capitation Reform in Rwanda
Babaniyi Olaniyi, Ina Kalisa, Ana Fernández del Río +9
As part of Rwanda's transition toward universal health coverage, the national Community-Based Health Insurance (CBHI) scheme is moving from retrospective fee-for-service reimbursem…
The Digital Transformation in Health: How AI Can Improve the Performance of Health Systems
África Periáñez, Ana Fernández del Río, Ivan Nazarov +4
Mobile health has the potential to revolutionize health care delivery and patient engagement. In this work, we discuss how integrating Artificial Intelligence into digital health a…
Adaptive User Journeys in Pharma E-Commerce with Reinforcement Learning: Insights from SwipeRx
Ana Fernández del Río, Michael Brennan Leong, Paulo Saraiva +5
This paper introduces a reinforcement learning (RL) platform that enhances end-to-end user journeys in healthcare digital tools through personalization. We explore a case study wit…
Adaptive Behavioral AI: Reinforcement Learning to Enhance Pharmacy Services
Ana Fernández del Río, Michael Brennan Leong, Paulo Saraiva +5
Pharmacies are critical in healthcare systems, particularly in low- and middle-income countries. Procuring pharmacists with the right behavioral interventions or nudges can enhance…
Optimizing HIV Patient Engagement with Reinforcement Learning in Resource-Limited Settings
África Periáñez, Kathrin Schmitz, Lazola Makhupula +6
By providing evidence-based clinical decision support, digital tools and electronic health records can revolutionize patient management, especially in resource-poor settings where…
Synthetic Data Generator for Adaptive Interventions in Global Health
Aditya Rastogi, Juan Francisco Garamendi, Ana Fernández del Río +4
Artificial Intelligence and digital health have the potential to transform global health. However, having access to representative data to test and validate algorithms in realistic…
Adaptive Interventions for Global Health: A Case Study of Malaria
África Periáñez, Andrew Trister, Madhav Nekkar +2
Malaria can be prevented, diagnosed, and treated; however, every year, there are more than 200 million cases and 200.000 preventable deaths. Malaria remains a pressing public healt…
Actionable Recourse via GANs for Mobile Health
Jennifer Chien, Anna Guitart, Ana Fernandez del Rio +2
Mobile health apps provide a unique means of collecting data that can be used to deliver adaptive interventions.The predicted outcomes considerably influence the selection of such…
User Engagement in Mobile Health Applications
Babaniyi Yusuf Olaniyi, Ana Fernández del Río, África Periáñez +1
Mobile health apps are revolutionizing the healthcare ecosystem by improving communication, efficiency, and quality of service. In low- and middle-income countries, they also play…
A Data-Centric Behavioral Machine Learning Platform to Reduce Health Inequalities
Dexian Tang, Guillem Francès, África Periáñez
Providing front-line health workers in low- and middle- income countries with recommendations and predictions to improve health outcomes can have a tremendous impact on reducing he…
A Recommendation System to Enhance Midwives' Capacities in Low-Income Countries
Anna Guitart, Afsaneh Heydari, Eniola Olaleye +4
Maternal and child mortality is a public health problem that disproportionately affects low- and middle-income countries. Every day, 800 women and 6,700 newborns die from complicat…
Midwifery Learning and Forecasting: Predicting Content Demand with User-Generated Logs
Anna Guitart, Ana Fernández del Río, África Periáñez +1
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. Dat…
A Time Series Approach To Player Churn and Conversion in Videogames
Ana Fernández del Río, Anna Guitart, África Periáñez
Players of a free-to-play game are divided into three main groups: non-paying active users, paying active users and inactive users. A State Space time series approach is then used…
Understanding Player Engagement and In-Game Purchasing Behavior with Ensemble Learning
Anna Guitart, Ana Fernández del Río, África Periáñez
As video games attract more and more players, the major challenge for game studios is to retain them. We present a deep behavioral analysis of churn (game abandonment) and what we…
Profiling Players with Engagement Predictions
Ana Fernández del Río, Pei Pei Chen, África Periáñez
The possibility of using player engagement predictions to profile high spending video game users is explored. In particular, individual-player survival curves in terms of days afte…
From Non-Paying to Premium: Predicting User Conversion in Video Games with Ensemble Learning
Anna Guitart, Shi Hui Tan, Ana Fernández del Río +2
Retaining premium players is key to the success of free-to-play games, but most of them do not start purchasing right after joining the game. By exploiting the exceptionally rich d…
The Winning Solution to the IEEE CIG 2017 Game Data Mining Competition
Anna Guitart, Pei Pei Chen, África Periáñez
Machine learning competitions such as those organized by Kaggle or KDD represent a useful benchmark for data science research. In this work, we present our winning solution to the…
Customer Lifetime Value in Video Games Using Deep Learning and Parametric Models
Pei Pei Chen, Anna Guitart, Ana Fernández del Río +1
Nowadays, video game developers record every virtual action performed by their players. As each player can remain in the game for years, this results in an exceptionally rich datas…
A Machine-Learning Item Recommendation System for Video Games
Paul Bertens, Anna Guitart, Pei Pei Chen +1
Video-game players generate huge amounts of data, as everything they do within a game is recorded. In particular, among all the stored actions and behaviors, there is information o…
Game Data Mining Competition on Churn Prediction and Survival Analysis using Commercial Game Log Data
EunJo Lee, Yoonjae Jang, DuMim Yoon +14
Game companies avoid sharing their game data with external researchers. Only a few research groups have been granted limited access to game data so far. The reluctance of these com…
Discovering Playing Patterns: Time Series Clustering of Free-To-Play Game Data
Alain Saas, Anna Guitart, África Periáñez
The classification of time series data is a challenge common to all data-driven fields. However, there is no agreement about which are the most efficient techniques to group unlabe…
Churn Prediction in Mobile Social Games: Towards a Complete Assessment Using Survival Ensembles
África Periáñez, Alain Saas, Anna Guitart +1
Reducing user attrition, i.e. churn, is a broad challenge faced by several industries. In mobile social games, decreasing churn is decisive to increase player retention and rise re…
Games and Big Data: A Scalable Multi-Dimensional Churn Prediction Model
Paul Bertens, Anna Guitart, África Periáñez
The emergence of mobile games has caused a paradigm shift in the video-game industry. Game developers now have at their disposal a plethora of information on their players, and thu…
Forecasting Player Behavioral Data and Simulating in-Game Events
Anna Guitart, Pei Pei Chen, Paul Bertens +1
Understanding player behavior is fundamental in game data science. Video games evolve as players interact with the game, so being able to foresee player experience would help to en…