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The next generation paradigm of medical AI
The world's leading builder of medical AI ecosystems
Leoht AI uses causal reasoning AI as the engine, zero-knowledge proof as the cornerstone of trust, and operations research optimization as the core of decision-making, reshaping the logic of drug research and development and promoting the medical industry's paradigm revolution towards a patient-centered, data-driven, and value-sharing
1.3M
50%
15+
Short R & D cycle
Disease exclusive Omics sample
Technology patents
Leoht AI
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Data Security
Zero-knowledge proof protection
Causal Reasoning
Beyond the limitations of traditional AI
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Full cycle-dynamic data-scientific research empowerment triple coupling
Leoht AI and medical experts provide patients with hierarchical interpretation of medical reports, and build a multi-terminal data system to assist in chronic disease management and clinical trials of pharmaceutical companies, achieving efficient patient recruitment and real-world data application
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Dynamic data tracking
Open up a closed loop of information on in-hospital and out-of-hospital treatment
Scientific research transformation empowerment
Build a bridge between medical resources and the needs of pharmaceutical companies
Full cycle patient services
Personalized support from report interpretation to plan adaptation
Technical barriers and industry genes
MediChain AI integrates three core technologies: causal reasoning, zero-knowledge proof, and operations research optimization to build complex advantages that are difficult to replicate and redefine the technical standards of medical AI
Zero-knowledge proof technology
Patients encrypt health data through ZKP and only provide 'data validity certificate' to the authorized party without exposing the raw data, ensuring that the data is available and invisible, and meeting compliance requirements
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Operations Research Optimization Engine
Dynamically optimize patient screening strategies through algorithms such as Markov decision process and integer programming, shortening the recruitment period by 30%+ and reducing trial and error costs by 50%
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Large model of causal reasoning
Deeply cultivate Do-Calculus, structural causality models (SCM), and counterfactual reasoning, break through the limitations of traditional AI'correlation analysis', and accurately analyze the causal relationship between drug-patient-disease
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0755-23482661
Room 1301, Northern Building, No. 3003 Shennan Middle Road, Futian District, Shenzhen
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info@andleoht.com
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