The paper identifies the need for integrating 'black box'

The gap

Evidence profile

Sourced from the recommendations and stated research gap and future-work section of the source papers, classified as general, spanning 6 journals. Those papers have been cited 2 times in total.

Supporting evidence — 8 representative gaps

• AI – Powered Personalization Care Recommendation Engine (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi

  utilized relevance of in order recommendation results. healthcare measures. to enhance The study plans to explore crucial issues related to healthcare AI systems like dataset biases, inability to provide transparent explanations for prediction results, possible ethical issues, and challenges in deployment. Most existing healthcare AI projects focus solely on prediction accuracy without taking other factors into account. Therefore, the purpose of the study is not to offer unrealistic claims about automation but to examine problems healthcare recommendation systems. like ethical AI-based issues with Another goal of this research is to explore some significant issues related to AI in the health sector 3 Somit Kumar Yadav, International Journal of Science, Engineering and Technology, 2026, 14:2 such as data bias, lack of explanation, ethics and implementation constraints. The main problem is that many current studies on AI and health care focus on high prediction accuracy without paying attention to other aspects like fairness and ethical deployment. Hence, this research focuses on the problems associated with AI-based health care recommendation systems. IV.

  generalrecommendationsevidence 5/5
  Keywords: healthcare issues recommendation systems like prediction ethical health explore related deployment focus accuracy without problems
• AI – Powered Personalization Care Recommendation Engine (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi

  Personalized recommendation engines often fail to incorporate the aspects of adaptability, recommendation ranking based on context, a scalable architecture for deployment, and prevention in healthcare. The vast majority of research done till now is mostly about predictions and not complete healthcare decision support ecosystems. Hence, this research attempts to fill these gaps through AI-powered personalized care recommendation engine. V.

  generalrecommendationsevidence 5/5
  Keywords: personalized recommendation healthcare powered care engine proposed engines often fail incorporate aspects adaptability ranking based
• AI – Powered Personalization Care Recommendation Engine (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi

  ranking based on context, a scalable architecture for deployment, and prevention in healthcare. The vast majority of research done till now is mostly about predictions and not complete healthcare decision support ecosystems. Hence, this research attempts to fill these gaps through AI-powered personalized care recommendation engine. V.

  generalrecommendationsevidence 5/5
  Keywords: healthcare powered personalized care engine proposed ranking based context scalable architecture deployment prevention vast majority
• Inteligência artificial aplicada à triagem automatizada em radiografias de tórax: uma abordagem com foco em explicabilidade (XAI) (2026) · OUTRAS PALAVRAS · doi

  The paper identifies a research gap in the application of artificial intelligence in healthcare, particularly in the use of explainable AI mechanisms. The study highlights the need for further research on the technical viability, diagnostic performance, statistical limitations, and ethical challenges of using artificial intelligence models.

  generalstated research gapevidence 5/5
  Keywords: paper identifies research gap application artificial intelligence healthcare
• Opportunities and Challenges in Using National EHR Networks for AI in Learning Health Systems (2026) · Learning Health Systems · cited 2× · doi

  Future research should investigate the effectiveness of AI models in clinical practice. Future research should examine the impact of data standardization and harmonization on AI development and deployment. Future research should explore the potential of national EHR networks to support personalized medicine and precision health.

  generalfuture-work sectionevidence 5/5
  Keywords: future research investigate effectiveness models clinical practice examine
• Ethical and social dynamics in artificial intelligence and society: A bibliometric study (2026) · Online Journal of Communication and Media Technologies · doi

  The study emphasizes the need for a more inclusive and interdisciplinary approach to AI ethics research. The study suggests that future research should prioritize the development of robust regulatory frameworks and governance structures to guarantee that AI-driven algorithms do not reinforce detrimental stereotypes or exacerbate social inequities.

  generalfuture-work sectionevidence 5/5
  Keywords: study emphasizes need inclusive interdisciplinary approach ethics research
• Overview of the future impact of wearables and AI in Healthcare workflows & technology (2026) · International Journal of Drug Delivery Technology · doi

  The gap in the mainstreaming of health processes due to concerns about privacy and security. The lack of effective analysis of wearable device data using AI algorithms to improve the accuracy of diagnoses and clinical decisions. The need for predictive analysis and custom-tailored designs for healthcare using wearable devices and AI algorithms.

  generalstated research gapevidence 5/5
  Keywords: gap mainstreaming health processes due concerns about privacy
• Recent Progress and Challenges of Digital Health and Bioengineering (2026) · Applied Sciences · doi

  The paper identifies the need for integrating 'black box' models into research and clinical workflows. The paper highlights the need for ensuring data privacy and mitigating biases in AI algorithms. The paper discusses the regulatory and liability issues associated with the use of AI in digital health and bioengineering.

  generalstated research gapevidence 5/5
  Keywords: paper identifies need integrating black box models research

Questions about this gap