Good Questions Meet Big Data

In July 2017, Translational Innovator issued a data ideation challenge: “Good Questions Meet Big Data.” Applicants were asked to identify a human health problem that might be resolved using big data and a computational solution. Entries were required to be problems that could be addressed with clinical and translational research in areas such as diagnostics, therapeutics, public health, technology, or outcomes.

A total of $10,000 in prizes were awarded to 11 winners.

Sponsoring Program

Translational Innovator


Sanjat Kanjilal | Optimizing Antibiotic Therapy through Machine Learning Models
Ramya Palacholla and Nils Fischer | Innovative Tumor Response Forecasting Model to Predict Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Patients
Jeremy Warner | The Challenge of Cancer Genomic Data Interpretation
Surojit Biswas | Leveraging Public Gene Expression Data and Machine-Learning for Efficient, High Yield Differentiation of iPSCs into Therapeutic Cell Populations
Prateek Prasanna | Big Data for Characterization of Brain Tumors: A Radiomics and Radiogenomics-Based Approach
Charlotta Lindvall | Incorporating the Patient’s Voice into Cancer Care and Research
Jan Heng | Automatic Classification of Clear Cell Renal Tumors Using Deep Learning: Implications for Diagnosis and Prediction of Metastasis
Rulla Tamimi | Computational Approaches to Assessing Breast Asymmetry for Early Detection of breast cancer