ODIN · Computer Vision AI + Bio-sciences (ODIN.org)

Team members:

“Narrow enhancing artificial intelligence will most likely help healthcare move from traditional, ‘one-size-fits-all’ medical solutions towards targeted treatments, personalised therapies,and uniquely composed drugs.”

-AllThingsD / WSJ, Dr. Patrick Riley, Ph.D.

ODIN (odin.org) is a lifesciences, computer vision AI research and development project whose mission is to harness advanced technologies to increase our understanding of the biology that controls lifespan. ODIN uses modern data and infomatics knowledge to devise interventions that enable people to lead longer and healthier lives. 

The potential for increased AI usage in bio-lifescience medicine is not just in a reduction of manual tasks and the freeing up of physician’s time, increasing efficiency and productivity - it also presents the opportunity for us to move towards more ‘precision medicine’.

Observe: Computer vision AI has the potential to empower medical professionals to provide significantly better analysis based on the algorithms of computer vision, testing and labs analysis, and improve overall longevity for end users.

Detect: The detection of biological disese, both early and late stage, is significantly augmented by computer vision detection, and provides a higher accuracy, both positive and false positive statistics, in numerous studies.

Identify: ODIN AI deliberately and sensibly identify those areas where automation could free up time and effort. The goal is a balance between the effective use of technology and AI and the human strengths and judgement of trained medical professionals.

Neutralize: ODIN AI makes recommendations for additional tests, or custom treatment designed for the unique individual and their observed, detected and identified conditions and data.


With ODIN's API, any software can:

1) Create and compare models based on your data.

2) Save and deploy a model.

3) Perform risk-adjusted comparisons.

4) Do trend analysis following Nelson rules.

5) Improve sparse data via longitudinal imputation.

6) Fill in missing data via imputation.

7) Deploy a model to produce daily predictions.

8) Write predictions back to a database.

9) Learn what factors drive each prediction.

10) Have a deeper understanding of the values of photographs, scans and biological analysis.


ODIN: BioAI.  Observe. Detect. Identity. Neutralize.

Last updated:

December 1, 2019