medicine9 papersavg year 2026moderate evidence

Improved risk prediction models in spine surgery

Research gap analysis derived from 9 medicine papers in our local library.

The gap

There is a need for improved risk prediction models in spine surgery that can accurately predict perioperative outcomes. Traditional risk models have limitations, including modest predictive performance and lack of generalizability. Artific

Evidence profile

Sourced from the future work and stated research gap and future-work section of the source papers, classified as general, spanning 6 journals.

Research trend

Established — well-defined area with open sub-problems.

Supporting evidence — 8 representative gaps

  • Radiomics and Artificial Intelligence in Breast Cancer Imaging: Future Directions and Clinical Applicability (2026) · Karnataka Journal of Surgery · doi

    Example: The future of AI in BC imaging lies in: • AI models achieved a diagnostic accuracy comparable to that of senior radiologists. • Some DL algorithms report an AUC > 0.90 for BC diagnosis in large screening datasets. AI for BC prognosis prediction AI extends beyond detection and diagnosis by predicting: • XAI: Transparent models for building trust among clinicians. •

    generalfuture workevidence 5/5
    Keywords: models diagnosis example future imaging lies achieved diagnostic accuracy comparable senior radiologists algorithms report large
  • AI-Powered Medical Devices: Innovation, Regulation, and Clinical Impact (2026) · International Journal of Medical and Health Research · doi

    The development of new AI-powered devices presents many new regulatory, legal, ethical and cyber security challenges to be addressed. There is a need for a risk-based approach for AI enabled healthcare devices. There is a need for future research on the integration of larger scale interdisciplinary approaches involving engineering, clinical science, regulatory policy, ethics and health informatics.

    generalstated research gapevidence 5/5
    Keywords: development new ai-powered devices presents many regulatory legal
  • AI-Powered Medical Devices: Innovation, Regulation, and Clinical Impact (2026) · International Journal of Medical and Health Research · doi

    The evolution of existing research approaches in intelligent diagnostics, patient monitoring systems, personalized medicine and AI regulated governance. Creating validated evaluation frameworks that can be uniformly used to assess AI tools and devices across the lifecycle. Identifying applicable methods for ongoing monitoring, real world evidence collection, and post market research.

    generalfuture-work sectionevidence 5/5
    Keywords: evolution existing research approaches intelligent diagnostics patient monitoring
  • Artificial intelligence in neurovascular surgery: advancing diagnosis, treatment, and outcomes (2026) · Frontiers in Surgery · doi

    The complexity of neurovascular pathologies and the variability in clinical presentation hinder timely and accurate diagnosis, precise risk stratification, and effective intervention. The limited generalizability of AI systems across heterogeneous clinical populations is a critical barrier to adoption. The reliance on imaging data alone is a key limitation, as comprehensive risk prediction requires integration with electronic health records.

    generalstated research gapevidence 5/5
    Keywords: complexity neurovascular pathologies variability clinical presentation hinder timely
  • Artificial intelligence in neurovascular surgery: advancing diagnosis, treatment, and outcomes (2026) · Frontiers in Surgery · doi

    Future research should focus on developing AI systems that can generalize across diverse clinical populations and integrate with electronic health records. The development of more robust and generalizable AI algorithms is necessary to improve diagnostic accuracy and risk prediction. The integration of AI with precision medicine and robotic-assisted microsurgery has the potential to improve patient outcomes and should be explored in future studies.

    generalfuture-work sectionevidence 5/5
    Keywords: future research focus developing systems generalize across diverse
  • REVIEW ON ARTIFICIAL INTELLIGENCE FOR DIABETES MANAGEMENT (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi

    Future research should focus on the development of more advanced AI algorithms for diabetes management. There is a need for further studies on the use of AI in diabetes diagnosis, treatment, and management. The integration of technology and AI can revolutionize the landscape of diabetes management, offering innovative solutions to enhance monitoring, improve treatment adherence, and provide personalized care.

    generalfuture-work sectionevidence 5/5
    Keywords: future research focus development advanced algorithms diabetes management
  • Leveraging Clinical Registries and Electronic Health Systems to Advance Value-Based Medicine Across Specialties (2026) · The Permanente Journal · doi

    The use of artificial intelligence and access to extensive registry databases and an integrated EHR are current and future areas of focus. Machine learning can be used to predict optimal, individualized surgical approaches for patients. International collaborations can provide opportunities for generating worldwide medical device evidence among international orthopedic registries.

    generalfuture-work sectionevidence 5/5
    Keywords: use artificial intelligence access extensive registry databases integrated
  • AI-based automated bleeding monitoring in conventional and robot-assisted laparoscopic surgery: a systematic review (2026) · Journal of Robotic Surgery · doi

    The review identified a gap in the current literature, with most studies relying on small, single-center datasets and retrospective validation. The study highlighted the need for further research to fully realize the potential of AI-based intraoperative bleeding monitoring. The review identified a need for more diverse and representative datasets to improve the generalizability of AI models.

    generalstated research gapevidence 5/5
    Keywords: review identified gap current literature studies relying small

Questions about this gap

There is a need for improved risk prediction models in spine surgery that can accurately predict perioperative outcomes. Traditional risk models have limitations, including modest… This is supported by 8 representative gap statements extracted from 9 papers, rated moderate evidence.

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