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auto-ml

Auto-ML python code for radiomics analysis

awesome-quant

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

captk

Cancer Imaging Phenomics Toolkit (CaPTk) is a software platform to perform image analysis and predictive modeling tasks. Documentation: https://cbica.github.io/CaPTk

coursera-ml-andrewng-notes

吴恩达老师的机器学习课程个人笔记

ctdna

This project involves liquid biopsy and lung CT imaging for the cancer patients. Target lesions (tumors) are manually segmented by Sharyn and we extracted radiomics features using pyradiomics.

dipy

Diffusion MR Imaging in Python

dl_radiomics_fusion

Comparison and fusion of deep learning and radiomics features of ground-glass nodules to predict the invasiveness risk of stage-I lung adenocarcinomas in CT scan

dmradiomics

Scripts to compute the features and fit radiomics models as used in the paper "Differential diagnosis and mutation stratification of desmoid tumors on MRI using a radiomics approach." M. J. M. Timbergen, M. P. A. Starmans et al. 2020.

ec-paper

This repository contains all python source code files to demonstrate how to conduct the machine learning described in the paper entitled "Machine Learning-Based Radiomics Analysis for Differentiation Degree and Lymphatic Node Metastasis of Extrahepatic Cholangiocarcinoma".

fmradio

Factor Modeling for radiomics

g.wu

gbm-radiogenomics

Identifying pathways underpinning prognostic radiomics in GBM

gbm-robustradiomics

Code accompanying the paper "Radiomics for glioblastoma survival analysis in pre-operative MRI: exploring feature robustness, class boundaries, and machine learning techniques"

gpt-llmmed

Large Language Models Streamline Automated Machine Learning for Clinical Studies

hcc-radiomics2022

lgg-1p-19q-deletion

lgg-radiomics

lgg_pd-l1

lppls

Library for fitting the LPPLS model to data.

markowitz

Python script that takes stocks in a portfolio and outputs the two Markowitz portfolios on the efficient frontier: Max Sharpe Ratio (MSR) portfolio allocation and Global Minimum Volatility (GMV) portfolio allocation

melaradiomics

Scripts to compute the radiomics features and fit the machine learning models as presented in the paper "The BRAF P.V600E Mutation Status of Melanoma Lung Metastases Cannot Be Discriminated on Computed Tomography by LIDC Criteria nor Radiomics Using Machine Learning." by L. Angus and M. P. A. Starmans et al. 2021.

mesentericradiomics

Scripts to compute the features and fit radiomics models as used in the paper: Blazevic, A., Starmans, M. P. A., Brabander, T., Dwarkasingh, R., van Gils, R., Hofland, J., Franssen, G. J., Feelders, R. A., Niessen, W. J., Klein, S., & de Herder, W. W. (2021). Predicting symptomatic mesenteric mass in neuroendocrine tumors using radiomics, Endocrine-Related Cancer, ERC-21-0064.

networkssession

All materials for the Networks practical of the 2019 Statistics for Omics course

o-raw

Ontology-guided Radiomics Analysis Workflow (O-RAW)

opbgdataset

pablo

Publicly Available Brain image anaLysis tOol kit

pandas-montecarlo

A lightweight Python library for running simple Monte Carlo Simulations on Pandas Series data

pyfolio

Portfolio and risk analytics in Python

pythonmlproject

Machine Learning Model: classifying malignant vs benign brain tumors

qlib

Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies.