Python-based Advanced Numerical Nonlinear Optimization for Radiotherapy

[MICCAI 2022] Official Implementation for "Hybrid Spatio-Temporal Transformer Network for Predicting Ischemic Stroke Lesion Outcomes from 4D CT Perfusion Imaging"

Training radiomics-based CNNs for clinical outcome prediction: Challenges, strategies and findings

Cusal Inference applied to timeseries, uses an event database to generate a timeseries of the outcome given a sliding window containing events. Useful to add causal outcomes of events into multivariate timeseries forecasting models.

Deeper IMPACT: Ordinal Models for Outcome Prediction After Traumatic Brain Injury

🧬🔍CNV analysis and outcome prediction in Ultra-High-Risk and First Episode Psychosis individuals 🩺🧠

TF2 match outcome prediction

COVID-19 outcome prediction models based on machine learning algorithms. The unique feature is a custom cross-validation strategy based on the three clinical datasets of age- and gender-matched patients.

Code repository for the paper entitled "Segmentation-Free Outcome Prediction in Head and Neck Cancer: Deep Learning-based Feature Extraction from Multi-Angle Maximum Intensity Projections (MA-MIPs) of PET Images" published in "Cancers" journal.

This repository contains a synthetic version of the MIMIC-III clinical database, recreated in SQLite3 for educational and analytical purposes. All personally identifiable information (PII) has been removed, and dummy data has been generated to simulate the schema and structure of the real dataset.