Algorithm for Collaboration & Distribution Case Study| Theta Tech Artificial Intelligence

‍Executive Summary:

A client had several papers written on clever new AI algorithms, but the underlying code was not professionally written nor efficient.
The client wished to share their research with their community, but did not feel comfortable sharing their code with collaborators.
Enter Theta Tech AI. Our team came in, fully understood their algorithm, both from a clinical as well as a technical perspective, and dove in.
We rewrote their code from scratch in modern Python with proper modularity, and then built a portfolio of sharable Jupyter Notebooks and Google Colabs for the client.
Our clients felt confident sharing this code with others, and had plenty of example outputs and visualizations to allow others to build atop this.
Without Theta Tech AI, their code would have stayed in the lab, and limited the client’s reach.

Key Benefits to Client:

Clinicians and researchers could confidently share professionally written, well-documented code, facilitating greater collaboration and accelerated scientific progress.
Clear modularity and easy-to-follow Jupyter notebooks enabled collaborators to replicate results effortlessly, increasing clinical trust in the underlying algorithms.
The updated, accessible codebase significantly expanded the client’s reach and impact, helping clinicians quickly adopt innovative AI techniques into their own practice and research.

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