⚠️ ARCHIVED ⚠️ Essential tools and utility functions to facilitate the data processing pipeline, data cleaning and data analysing of clinical data from CC-HIC

ISeeU: Visually interpretable deep learning for mortality prediction inside the ICU

This project is an independent approach to acquire patient data from Philips patient monitors via network interface.

Public code from paper: 'Towards a decision support tool for intensive care discharge: machine learning algorithm development using electronic healthcare data from MIMIC-III and Bristol, UK'

Medical calculator for intensive care unit

Code for data linkage (curation of research database).

Python package to detect AKI within time series data.

Using data within first 24 hours of intensive care to develop a machine learning model that could improve the current patient survival probability prediction system (apache_4a) and is more generalized to patients outside of the US

It is a system that collects patient information with the help of a few sensors using WiFi module to keep the Doctors updated all time over internet

Unsupervised Learning Approaches for Identifying ICU Patient Subgroups: Do Results Generalise?

WPF App for controlling and monitoring the system.

Assessing the computational reproducibility of Wood et al. 2021 as part of STARS.

Code for the analysis of mortality progression in COVID-19 ICU hospitalizations in Brazil (Rede D'Or São Luiz)

Observational study of central venous catheter-related thrombosis

Buap, México. Facultad de Cultura Física: La app crea dos ecuaciones de regresión múltiple sobre Frecuencia Cardíaca Máxima y Frecuencia Cardíaca en Reposo y usa la formula de Karvonen para encontrar los LPM según varias intensidades de carga deseadas. Con la opción de crear ecuaciones automáticas para datos específicos de grupos específicos de …

My implementation of a Reinforcement Learning framework for Sepsis management.

This project is intended to provide some useful tools to the daily work of physicians on the intensive care unit.

Temporal Variational Autoencoder Model for Rapid Response Sytem

Assessing the computational reproducibility of Anagnostou et al. 2022 as part of STARS.