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Explainable Artificial Intelligence Recommendation System by Leveraging
  the Semantics of Adverse Childhood Experiences: Proof-of-Concept Prototype
  Development

Explainable Artificial Intelligence Recommendation System by Leveraging the Semantics of Adverse Childhood Experiences: Proof-of-Concept Prototype Development

6 November 2020
Nariman Ammar
Arash Shaban-Nejad
ArXiv (abs)PDFHTML

Papers citing "Explainable Artificial Intelligence Recommendation System by Leveraging the Semantics of Adverse Childhood Experiences: Proof-of-Concept Prototype Development"

4 / 4 papers shown
Title
A Joint-Reasoning based Disease Q&A System
A Joint-Reasoning based Disease Q&A System
Prakash Chandra Sukhwal
Vaibhav Rajan
A. Kankanhalli
LM&MAAI4MH
51
0
0
06 Jan 2024
On Explainability in AI-Solutions: A Cross-Domain Survey
On Explainability in AI-Solutions: A Cross-Domain Survey
S. D. Antón
Daniel Schneider
Hans D. Schotten
57
2
0
11 Oct 2022
An Urban Population Health Observatory for Disease Causal Pathway
  Analysis and Decision Support: Underlying Explainable Artificial Intelligence
  Model
An Urban Population Health Observatory for Disease Causal Pathway Analysis and Decision Support: Underlying Explainable Artificial Intelligence Model
Whitney S. Brakefield
Nariman Ammar
A. Shaban-Nejad
63
9
0
26 Jul 2022
Using a Personal Health Library-Enabled mHealth Recommender System for
  Self-Management of Diabetes Among Underserved Populations: Use Case for
  Knowledge Graphs and Linked Data
Using a Personal Health Library-Enabled mHealth Recommender System for Self-Management of Diabetes Among Underserved Populations: Use Case for Knowledge Graphs and Linked Data
Nariman Ammar
J. Bailey
R. Davis
Arash Shaban-Nejad
18
27
0
16 Mar 2021
1