Featured research

Evidence behind the platform

Peer-reviewed publication

The Advanced Health Risk Predictor: Ensemble Machine Learning System for Multi Disease Clinical Decision Support

Venue
IEEE AIIoT 2026
Award
Best Presenter — Session 5
Awarded to Shruti Bhandari

This paper presents an ensemble machine learning architecture for multi-disease clinical decision support, demonstrating the research methodology underlying Medisight's diagnostic intelligence layer.

Independent benchmark

MedAgentBench Evaluation

RankModelOrgAccuracy
0DeepSeek-V4-FlashMedisight
99%+
🥇Grok 4.6Medicalsphere
95.9%
🥈GPT-5.6 SolMedicalsphere
94.7%
🥉Grok 4.5Medicalsphere
93.4%

99%+ across all 10 EHR task categories using DeepSeek-V4-Flash, an open-weight model. Competitor scores from the MedicalSphere public leaderboard (Aug 2026).

Doctor reviewing clinical information with a patient
For your team

What this means for you

Independent evidence helps your team evaluate accuracy, reliability, and value before deployment.

  • Evidence you can defend

    Peer-reviewed research gives clinical and procurement teams credible evidence when evaluating the platform.

  • High accuracy at an accessible cost

    A 99%+ MedAgentBench score demonstrates strong performance without relying on a premium closed model.

  • Faster validation, less guesswork

    Direct links to publications, benchmarks, and pilot outcomes make every claim easier to verify and share.

Pilot partners

Results in the field

Pilot deployments across healthcare and research settings. Outcomes describe specific engagements and may not reflect typical results.

  • Medicise SA

    Medicise SA

    Clinical Practice · Pilot

    Challenge

    Manually reviewing complex cardiopulmonary exercise data slowed clinicians down.

    Solution

    Real-time dashboards and AI-assisted agents built for exercise physiology workflows.

    Outcome

    Faster review, same clinical control

    Higher-resolution views surfaced patterns clinicians could act on immediately.

    Pilot deployment · illustrative results

  • Caleo Biotechnologies

    Caleo Biotechnologies

    Biotechnology Research · Pilot

    Challenge

    Manual cell-image interpretation bottlenecked research throughput and reproducibility.

    Solution

    AI-assisted image analysis for cell segmentation, morphology, and stain quantification.

    Outcome

    Days → Minutes in analysis time

    The team processed a full image set with consistently reproducible results.

    Pilot deployment · illustrative results

  • Janelia Research Campus

    Janelia Research Campus

    Advanced Research Institute · Pilot

    Challenge

    Diverse datasets meant manual handling and inconsistent workflows across research groups.

    Solution

    A universal data platform with automated visualization and one-click reporting.

    Outcome

    Hours → Seconds in dataset analysis

    Every research group now runs the same fast, consistent analysis pipeline.

    Pilot deployment · illustrative results