Metadata-Version: 2.1
Name: eslearn
Version: 1.0.26
Summary: This project is designed for machine learning in resting-state fMRI field
Home-page: https://github.com/easylearn-fmri/
Author: Chao Li; Mengshi Dong
Author-email: lichao19870617@gmail.com
Maintainer: Chao Li; Mengshi Dong
Maintainer-email: lichao19870617@gmail.com
License: MIT License
Description: Easylearn is designed for machine learning mainly in resting-state fMRI, radiomics and other fields (such as EEG). Easylearn is built on top of scikit-learn, pytorch and other packages. Easylearn can assist doctors and researchers who have limited coding experience to easily realize machine learning, e.g., (MR/CT/PET/EEG)imaging-marker- or other biomarker-based disease diagnosis and prediction, treatment response prediction, disease subtyping, dimensional decoding for transdiagnostic psychiatric diseases or other diseases, disease mechanism exploration and etc.  
        
        We focus on machine learning rather than data preprocessing. Many software, such as SPM, GRETNA, DPABI, REST, RESTPlus, CCS, FSL, Freesufer, nipy, nipype, nibabel, fmriprep and etc, can be used for data preprocessing.  
        
        # Citing information:
        If you think this software (or some function) is useful, citing the easylearn software in your paper or code would be greatly appreciated!
        Citing link: https://github.com/lichao312214129/easylearn 
        
        # Install  
        ```
        pip install -U eslearn
        ```
        
        # Usage
        ```
        import eslearn as el
        el.run()
        ```
        
        # Development    
        We hope you can join us!     
        > Email: lichao19870617@gmail.com  
        > Wechat: 13591648206  
        
        # Supervisors/Consultants 
        
        ##### Ke Xu
            kexu@vip.sina.com  
            Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China.  
            Department of Radiology, The First Affiliated Hospital of China Medical University.
        
        ##### Yanqing Tang  
            yanqingtang@163.com  
            1 Brain Function Research Section, The First Affiliated Hospital of China Medical
            University, Shenyang, Liaoning, PR China.  
            2 Department of Psychiatry, The First Affiliated Hospital of China Medical University,
            Shenyang, Liaoning, PR China.        
            
        ##### Yong He  
            yong.he@bnu.edu.cn  
            1 National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China  
            2 Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China  
            3 IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China 
        
        # Maintainers
        ##### Chao Li
            lichao19870617@gmail.com
            Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China.  
            
        ##### Mengshi Dong
            dongmengshi1990@163.com  
            Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China.  
        
Platform: all
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: Natural Language :: English
Classifier: Natural Language :: Chinese (Simplified)
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.5
Description-Content-Type: text/markdown
