prognostic-models

The NASA Prognostic Python Packages is a Python framework focused on defining and building models and algorit for prognostics (computation of remaining useful life) of engineering systems, and provides a set of models and algorithms for select components developed within this framework, suitable for use in prognostic applications.

The NASA Prognostic Model Package is a Python framework focused on defining and building models for prognostics (computation of remaining useful life) of engineering systems, and provides a set of prognostics models for select components developed within this framework, suitable for use in prognostics applications for these components.

This is the official repository of the R package metamisc

A missing-aware multimodal framework that fuses CT, Whole-Slide Histopathology, and clinical tabular data for survival prediction in unresectable stage II–III Non-Small Cell Lung Cancer (NSCLC) — without dropping patients or imputing absent modalities.

Reproduce results from the paper "Development, validation and clinical usefulness of a prognostic model for relapse in relapsing-remitting multiple sclerosis. K. Chalkou et. al. Diagn Progn Res . 2021 Oct 27;5(1):17. doi: 10.1186/s41512-021-00106-6."

Pronostic biomarkers for SKCM

Anomaly Detection in Time Series Data using Autoencoders approach.

🩺 Multi-method ML diagnostic & prognostic classifier using ensemble learning (RF, SVM, XGBoost, KNN, MLP) with permutation testing, feature selection, and profile ranking

Effect of socioeconomic status in mortality rates after brain injury: cohort study

Time-adjusted effect of socioeconomic status in mortality rates after brain injury: cohort study

Sensitivity of mortality rates to the imputation of missing socioeconomic data: cohort study

NASA Turbofan Jet Engine Propagation modeling

Conceptual models of oceanic diurnal warm layer dynamics

Retrospective cohort survival analysis of time-to-full-weight-bearing (FWB) in adult lower extremity fracture patients. Cox PH regression Built with R .

Met-Score for predicting metastasis in prostate cancer from primary tumor gene expression profiles

[MICCAI 2024] novel Multi-Dataset Multi-Task (MDMT) learning framework that predicts COVID-19 prognostic outcomes from chest X-rays by jointly training on two publicly available datasets with distinct but correlated labelling schemes, AIforCOVID and BRIXIA, without requiring universal cross-dataset annotations.

Consultorias em Estatística Médica e Epidemiologia Clínica. CNPJ:42.154.074/0001-22

Predicting Remaining Useful Life (RUL) of jet engines using NASA’s CMAPSS FD001 multivariate time-series sensor data.