Company: LNAI
Filing Date: 2025-05-15
Form Type: 10-Q
Source: 0001731122-25-000765
Chunk: 146

Company: Lunai Bioworks Inc.
Filing Date: 2025-05-15
Form: 10-Q
Item: Part I, Item 2
Chunk 146
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, but also integrates validated panels for different cancer types into
the “RenovaroCube” machine learning library. This process enables precision diagnosis, by including one cancer and excluding
others based on statistically, scientifically and clinically validated machine-learning panels.

Panel mining is designed to combine
biomarkers into panels in such a way that the final panel meets:

    ●
    performance metric criteria;

    ●
    technical criteria, such as a minimum or maximum number of biomarkers for the selected assay;

    ●
    biological criteria, non-annotated genes inclusion; and

    ●
    stratification criteria.

Explainable AI

The term “Explainable AI”
refers to the ability of an AI system or model to provide human-understandable explanations for its decision-making process or predictions.
This feature aims to bridge the gap between the “black box” nature of many AI algorithms and the need for transparency, interpretability,
and accountability in AI applications.

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In traditional machine learning
approaches, such as deep neural networks, the internal workings of the model can be complex and difficult to interpret. This lack of interpretability
poses challenges in critical domains where decisions have significant implications, such as healthcare.

Renovaro Cube believes that Explainable
AI is crucial for ensuring transparency, fairness, and accountability in AI systems. Renovaro Cube’s AI platform includes Explainable
AI by design. All data points, calculations and results are traceable, and all calculations are verifiable and reproducible with the same
result.

Disease prognosis is one of the
diagnostic capabilities of the Explainable AI feature of Renovaro Cube’s technology. Disease prognosis gives more insight for a
specific patient that empowers healthcare providers, patients, and their families to make well-informed decisions about treatment, care,
and future planning, thereby enhancing patient-centered care, optimizing resource utilization, and contributing to improved patient outcomes
and quality of life.

Differential Diagnosis

Renovaro Cube’s AI platform
offers differential diagnosis by design due to its approach with a multitude of models for different diseases and the ability to include
and exclude diseases.

Diseases like cancer are very homogenous,
meaning that markers like TP53 or BRCA are expressed with multiple cancers. To address this homogeneity, differential diagnosis distinguishes
between two or more conditions or diseases that share similar signs, symptoms or characteristics. The goal of differential diagnosis is
to consider and evaluate all possible diagnoses for the patient’s symptoms to determine the most likely cause