With the increasing complexity and multidimensionality of medical research data, traditional statistical methods are becoming more and more difficult in analysis. Visualization can present data in an intuitive, visual, and easy-to-read format, which helps medical researchers understand data, and discover scientific views from the interpretation of data.

Live Example: Cell Diagnostic Results for Five Patients

•What can an MD derive from this small dataset with no external synthetic control ?

•How can this small data be visualized by Artificial Intelligence?

Table 1.

Relations between '%' in healthy donors, Flow Cytometry Forward Scatter(AU),Flow Cytometry Side Scatter(AU) CD45 level(Mean), CD3 Level(Mean), and Natural Killers, T killer, T helper, B cell

That is what Doctor sees WITHOUT AIDATO :
Relation between B cell CD45 and T Helper and T Killer are
incomprehensible and confusing

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That is what Doctor sees WITH AIDATO :
Correlation between B cell CD45 and T Helper and T Killer are
‍clear and understandable

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We can also show other Multidimensional Data Visual (MDV) charts

Using unique AIDATO small data analysis methods. the following graphical correlations have been obtained

CD3, Natural Killers

Visual correlation of CD3 was derived from subset data of Table 1. Relations between CD3 Level(Mean) and Flow Cytometry Forward Scatter(AU),Flow Cytometry Side Scatter(AU) for Natural Killers

CD45, T Killers

Visual correlation of CD3 was derived from subset data of Table 1. Relations between CD3 Level(Mean) and Flow Cytometry Forward Scatter(AU),Flow Cytometry Side Scatter(AU) for Natural Killers

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