mlsanityData to 7 Oct 2026

A Comprehensive Scoping Review of Bayesian Networks in Healthcare: Past, Present and Future

arXiv 2002.08627 ↗First posted 20 Feb 2020cs.AIcited by 22

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Abstract (arXiv)

No comprehensive review of Bayesian networks (BNs) in healthcare has been published in the past, making it difficult to organize the research contributions in the present and identify challenges and neglected areas that need to be addressed in the future. This unique and novel scoping review of BNs in healthcare provides an analytical framework for comprehensively characterizing the domain and its current state. The review shows that: (1) BNs in healthcare are not used to their full potential; (2) a generic BN development process is lacking; (3) limitations exists in the way BNs in healthcare are presented in the literature, which impacts understanding, consensus towards systematic methodologies, practice and adoption of BNs; and (4) a gap exists between having an accurate BN and a useful BN that impacts clinical practice. This review empowers researchers and clinicians with an analytical framework and findings that will enable understanding of the need to address the problems of restricted aims of BNs, ad hoc BN development methods, and the lack of BN adoption in practice. To map the way forward, the paper proposes future research directions and makes recommendations regarding BN development methods and adoption in practice.

Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Feb 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 6; 2023: 2; 2024: 4; 2025: 6; 2026: 4.

22 papers.

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  1. 2023pgmpy: A Python Toolkit for Bayesian Networkscited by 21
  2. 2024bnRep: A repository of Bayesian networks from the academic literaturecited by 9
  3. 2024SimSUM: Simulated Benchmark with Structured and Unstructured Medical Recordscited by 6
  4. 2024Clinical Reasoning over Tabular Data and Text with Bayesian Networkscited by 4
  5. 2025FedGES: A Federated Learning Approach for BN Structure Learningcited by 4
  6. 2022Bayesian Networks for the robust and unbiased prediction of depression and its symptoms utilizing speech and multimodal datacited by 3
  7. 2022Fast Parallel Bayesian Network Structure Learningcited by 3
  8. 2022A hybrid Bayesian network for medical device risk assessment and managementcited by 2
  9. 2025Stable Structure Learning with HC-Stable and Tabu-Stable Algorithmscited by 2
  10. 2026Dynamic Expert-Guided Model Averaging for Causal Discoverycited by 2
  11. 2025A multimodal Bayesian Network for symptom-level depression and anxiety prediction from voice and speech datacited by 1
  12. 2026Structural Dimension Reduction in Bayesian Networkscited by 1
10 more
  1. 2022Motivating explanations in Bayesian networks using MAP-independencecited by 0
  2. 2022Neural Bayesian Network Understudycited by 0
  3. 2022Bayesian Network Models of Causal Interventions in Healthcare Decision Making: Literature Review and Software Evaluationcited by 0
  4. 2023Semantic web technologies in sensor-based personal health monitoring systems: A systematic mapping studycited by 0
  5. 2024A SAT-based approach to rigorous verification of Bayesian networkscited by 0
  6. 2025Structural Refinement of Bayesian Networks for Efficient Model Parameterisationcited by 0
  7. 2025Patient-level Information Extraction by Consistent Integration of Textual and Tabular Evidence with Bayesian Networkscited by 0
  8. 2025Scalable Bayesian Network Structure Learning Using Tsetlin Machine to Constrain the Search Spacecited by 0
  9. 2026How Does Bayesian Causal Discovery Fail? Characterising Structural Consequences in Linear Gaussian Networks under Latent Confoundingcited by 0
  10. 2026The Cost of Binarizing Survival Outcomes in Clinical Prognostic Modelingcited by 0