Clinical Decision Support System (CDSS)
Algorithmic Precision in Dermato-Oncology.
Operationalizing the riSCC prognostic model. The system integrates advanced statistical oncology with cloud computing to support real-time clinical decisions.
Client recommendation
Anokhi Jambusaria MD, MSCE
Division of Dermatology
Associate Professor, Department of Internal Medicine
Section Chief, General Dermatology, Department of Internal Medicine
Deputy Service Line Lead, Adult Dermatology, Ascension Medical Group
Dell Medical School | The University of Texas at Austin · dellmed.utexas.edu
I can wholeheartedly recommend this team! They are very easy to work with—communicative, responsible, and flexible. As someone who had never created a website before, they walked me through each step and provided us with a realistic estimate and timeline. And at the end of it all, they were able to deliver the product on time and under budget! I cannot say enough great things about them. 5 out of 5 stars!!
Evidence-Based Medicine
Data Foundation: N=23,166 Cohort.
Digital adaptation of a multi-center study on Cutaneous Squamous Cell Carcinoma (CSCC).
The tool implements the novel riSCC prognostic model (PMID: 40024391), developed based on a retrospective analysis from 1991–2023. The study spanned 12 international oncology centers, redefining risk stratification standards.
Jambusaria-Pahlajani A, et al. riSCC: A personalized risk model for the development of poor outcomes in cutaneous squamous cell carcinoma. J Am Acad Dermatol. 2025.
Research Consortium Partners:
Architecture: The Symbiosis of R and AWS SageMaker.
The engineering challenge was operationalizing Fine-Gray models from academia (R language) into scalable production infrastructure.
We designed a Serverless architecture that separates the logic layer from the compute layer. This enables real-time inference while maintaining rigorous medical data security standards.
Functionality Engineered for the Clinic.
The system eliminates information noise, delivering precise risk stratification within the timeframe of a standard patient visit.
Transforming Medical Knowledge into Technology.
Need a partner who understands both clinical rigor and cloud architecture?
Consult on MedTech Implementation