{"payload":{"pageCount":1,"repositories":[{"type":"Public","name":"PACS2go","owner":"frankkramer-lab","isFork":false,"description":"Towards a Portable Research PACS for Interdisciplinary Collaboration","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":3,"forksCount":0,"license":"GNU General Public License v3.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-06-01T15:46:14.383Z"}},{"type":"Public","name":"aucmedi","owner":"frankkramer-lab","isFork":false,"description":"a framework for Automated Classification of Medical Images","allTopics":["docker","framework","research","computer-vision","tensorflow","pip","automl","clinical-decision-support","medical-image-analysis","explainable-ai","healthcare-imaging","medical-image-classification","python","deep-learning","image-classification"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":1,"issueCount":51,"starsCount":34,"forksCount":9,"license":"GNU General Public License v3.0","participation":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,29,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-30T16:16:46.892Z"}},{"type":"Public","name":"RadTA","owner":"frankkramer-lab","isFork":false,"description":"RADiomics Trend Analysis for CT scans","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":0,"license":"GNU General Public License v3.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-29T08:20:38.958Z"}},{"type":"Public","name":"DeepGleason","owner":"frankkramer-lab","isFork":false,"description":"a System for Automated Gleason Grading of Prostate Cancer using Deep Neural Networks","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":3,"forksCount":2,"license":"GNU General Public License v3.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-03-25T12:19:26.990Z"}},{"type":"Public","name":"GERNERMED-pp","owner":"frankkramer-lab","isFork":false,"description":"GERNERMED++ is a transfer-learning-based open neural NER model for medical entities designed for German data.","allTopics":["nlp","natural-language-processing","information-extraction","spacy","named-entity-recognition","clinical-notes","ner","nlp-machine-learning","slot-filling","medical-informatics"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":7,"forksCount":2,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-10-20T12:35:42.285Z"}},{"type":"Public","name":"GERNERMED","owner":"frankkramer-lab","isFork":false,"description":"GERNERMED is the first open neural NER model for medical entities designed for German data.","allTopics":["clinical-notes","medical-informatics","nlp","natural-language-processing","information-extraction","spacy","named-entity-recognition","ner","nlp-machine-learning"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":17,"forksCount":5,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-10-20T12:30:53.384Z"}},{"type":"Public","name":"GPTNERMED","owner":"frankkramer-lab","isFork":false,"description":"GPTNERMED is a language model-generated, synthetic dataset and an open neural NER model for medical entities designed for German data.","allTopics":["nlp","natural-language-processing","german","information-extraction","spacy","dataset","transformer","named-entity-recognition","gpt","clinical-notes","ner","language-model","nlp-machine-learning","medical-informatics"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":15,"forksCount":1,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-10-05T15:21:29.429Z"}},{"type":"Public","name":"MIScnn","owner":"frankkramer-lab","isFork":false,"description":"A framework for Medical Image Segmentation with Convolutional Neural Networks and Deep Learning","allTopics":["framework","computer-vision","neural-network","tensorflow","medical-imaging","pip","medical-image-processing","clinical-decision-support","medical-image-analysis","medical-image-segmentation","healthcare-imaging","deep-learning","segmentation","convolutional-neural-networks"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":4,"issueCount":54,"starsCount":397,"forksCount":117,"license":"GNU General Public License v3.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-05-10T14:52:31.374Z"}},{"type":"Public","name":"covid19.MIScnn","owner":"frankkramer-lab","isFork":false,"description":"Robust Chest CT Image Segmentation of COVID-19 Lung Infection based on limited data","allTopics":["computer-vision","deep-learning","tensorflow","medical-imaging","medical-image-processing","lung-segmentation","u-net","medical-image-analysis","pneumonia","lung-disease","covid-19","lung-lobes","covid-19-ct","healthcare-imaging","segmentation","infection","3d-unet"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":2,"issueCount":6,"starsCount":86,"forksCount":31,"license":"GNU General Public License v3.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-03-25T01:05:45.878Z"}},{"type":"Public","name":"MISITcms","owner":"frankkramer-lab","isFork":true,"description":"Contest Management System","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":1,"issueCount":0,"starsCount":0,"forksCount":354,"license":"GNU Affero General Public License v3.0","participation":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-03-06T14:59:42.918Z"}},{"type":"Public","name":"ensmic","owner":"frankkramer-lab","isFork":false,"description":"An analysis on Ensemble Learning optimized Medical Image Classification with Deep Convolutional Neural Networks","allTopics":["deep-learning","study","image-classification","ensemble-learning","stacking","bagging","augmenting"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":17,"forksCount":2,"license":"GNU General Public License v3.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-07-19T10:48:36.808Z"}},{"type":"Public","name":"riadd.aucmedi","owner":"frankkramer-lab","isFork":false,"description":"Multi-Disease Detection in Retinal Imaging based on Ensembling Heterogeneous Deep Learning Models","allTopics":["deep-learning","ensemble-learning","class-imbalance","retinal-images","medical-image-analysis","multi-label-image-classification","healthcare-imaging","retinal-disease-detection"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":6,"starsCount":29,"forksCount":10,"license":"GNU General Public License v3.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-07-19T10:47:19.766Z"}},{"type":"Public","name":"NuCLS.MIScnn","owner":"frankkramer-lab","isFork":true,"description":"Nucleus segmentation and analysis of breast cancer using the MIScnn Framework and the NuCLS dataset.","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":1,"forksCount":1,"license":"GNU General Public License v3.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-06-17T09:58:27.461Z"}},{"type":"Public","name":"miseval.analysis","owner":"frankkramer-lab","isFork":false,"description":"Source code for the publication: Towards a Guideline for Evaluation Metrics in Medical Image Segmentation","allTopics":["guideline","evaluation","image-segmentation","reproducibility","semantic-segmentation","medical-image-analysis","performance-assessment"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":9,"forksCount":1,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-05-11T22:05:48.403Z"}},{"type":"Public","name":"gene-expression-on-fhir","owner":"frankkramer-lab","isFork":false,"description":"Implementing semantic interoperability of gene expression profiles using the HL7 FHIR standard","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":1,"forksCount":0,"license":"GNU General Public License v3.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-02-11T23:20:35.036Z"}}],"repositoryCount":15,"userInfo":null,"searchable":true,"definitions":[],"typeFilters":[{"id":"all","text":"All"},{"id":"public","text":"Public"},{"id":"source","text":"Sources"},{"id":"fork","text":"Forks"},{"id":"archived","text":"Archived"},{"id":"template","text":"Templates"}],"compactMode":false},"title":"Repositories"}