Topic: prostate-cancer Goto Github
Some thing interesting about prostate-cancer
Some thing interesting about prostate-cancer
prostate-cancer,🧠 A deep learning algorithm based on convolutional neural networks to detect glandular cells in digitalized biopsies of the prostate. Performed as bachelor thesis for the degree in computer engineering.
User: alvarillo89
prostate-cancer,
User: amatov
Home Page: http://www.uriwatch.com
prostate-cancer,A package providing MATLAB programming tools for IVIM-DKI analysis with total variation (TV) penalty function.
User: amitvmehndiratta
prostate-cancer,Fully supervised, healthy/malignant prostate detection in multi-parametric MRI (T2W, DWI, ADC), using a modified 2D RetinaNet model for medical object detection, built upon a shallow SEResNet backbone.
User: anindox8
prostate-cancer,Public release of ProstAttention-Net: A deep attention model for prostate cancer segmentation by aggressiveness in MRI scans
User: audreyduran
prostate-cancer,Code for the Cancers paper (Functional Linkage of RKIP to the Epithelial to Mesenchymal Transition and Autophagy during the Development of Prostate Cancer)
Organization: bcmslab
Home Page: https://www.mdpi.com/2072-6694/10/8/273/htm
prostate-cancer,Awesome artificial intelligence in cancer diagnostics and oncology
User: cbailes
prostate-cancer,Pytorch implementation of carcino-net
User: cielal
prostate-cancer,Hierarchical probabilistic 3D U-Net, with attention mechanisms (—𝘈𝘵𝘵𝘦𝘯𝘵𝘪𝘰𝘯 𝘜-𝘕𝘦𝘵, 𝘚𝘌𝘙𝘦𝘴𝘕𝘦𝘵) and a nested decoder structure with deep supervision (—𝘜𝘕𝘦𝘵++). Built in TensorFlow 2.5. Configured for voxel-level clinically significant prostate cancer detection in multi-channel 3D bpMRI scans.
Organization: diagnijmegen
prostate-cancer,Here I tried various Machine Learning algorithms on different cancer's dataset present in CSV format.
User: digamjain
prostate-cancer,ProLesA-Net: a Deep learning model For Prostate Lesion Segmentation from bi-parametric MR-Images
User: dzaridis
prostate-cancer,I proved the probabilities of freedom from biochemical recurrence (BCR) among prostate cancer patients are significantly different using stratified Logrank test. I also built a Cox's PH model to identify which genes and demographic factors have effect on survival.
User: ensembles4612
prostate-cancer,My 120th place solution to the PANDA Challenge hosted on Kaggle 🔬
User: greatgamedota
Home Page: https://www.kaggle.com/c/prostate-cancer-grade-assessment
prostate-cancer,Prostate segmentation in Micro-Ultrasound images using deep neural networks
User: guowenbin90
prostate-cancer,A model to predict Prostate Cancer using malignant and benign labeled MRI images.
User: hakanskn
prostate-cancer,His study addresses these concerns by predicting prostate cancer using six (6) machine learningtechniques: Random Forest, SVM, KNN, Logistic Regression, Neutral Network, and the Ensemble model. We gathered data from 100 patients who were placed in ten different circumstances. The data was categorised as malignant or non-cancerous. Among the six machine learning techniques, logistic regression, neuralnetworks, and ensemble learning have the potential to reach an accuracy of 95.00 percent. Ensemble learning can detect 96.55%of true positive prostate cancer in our model. KNN has a 90%accuracy rate, whereas SVM and Random Forest have an 85%accuracy rate.
User: hasansust32
prostate-cancer,This repository includes the code for the paper "Detection of Prostate Cancer with Multi-Parametric MRI Utilizing the Anatomic Structure of the Prostate".
User: jin93
prostate-cancer,Scripts for reproducing the poster: Co-regulation of RKIP and autophagy genes by VEZF1 and ERCC6 in prostate cancer
User: mahshaaban
prostate-cancer,Using biological constraints to improve the performance of transcriptomic gene signatures
Organization: marchionnilab
prostate-cancer,Distinct mesenchymal cell states mediate prostate cancer progression
User: mohamedomar2020
prostate-cancer,Automated reference tissue normalization of T2-weighted MR images of the prostate using object recognition
Organization: ntnu-mr-cancer
Home Page: https://link.springer.com/article/10.1007%2Fs10334-020-00871-3
prostate-cancer,The Reproducibility of Deep Learning-Based Segmentation of the Prostate Gland and Zones on T2-Weighted MR Images
Organization: ntnu-mr-cancer
Home Page: https://www.mdpi.com/2075-4418/11/9/1690
prostate-cancer,Fitting of three diffusion models to data acquired using combined T2-DWI.
Organization: ntnu-mr-cancer
prostate-cancer,8q24 finemapping results
Organization: oncogenetics
prostate-cancer,An interactive graphical illustration of genetic associations and their biological context
Organization: oncogenetics
prostate-cancer,NGS projects summary
Organization: oncogenetics
prostate-cancer,TensorFlow implementation of our paper: "Automated detection of aggressive and indolent prostate cancer on magnetic resonance imaging [Medical Physics 2021]".
Organization: pimed
prostate-cancer,Domain Generalization for Prostate Segmentation in Transrectal Ultrasound Images: A Multi-center Study
Organization: pimed
Home Page: https://pubmed.ncbi.nlm.nih.gov/36148705/
prostate-cancer,Prostate lesion classification using Deep Convolutional Neural Networks
User: piotrsobecki
prostate-cancer,Expression, biological and clinical relevance of the collagen pathway genes in prostate carcinoma
User: piotrtymoszuk
prostate-cancer,A wrapper containing search algorithm of Forward Selection + Pattern Classifier of KNN to use optimal features in prostate cancer
User: pirata-codex
prostate-cancer,Final Project - Post Genomic Analysis
User: raisa-nn
prostate-cancer,Train and Predict Cancer Subtype with Keras Model based on Mutational Signatures
User: shixiangwang
prostate-cancer,Research on a unified shape-based framework for faster extraction of prostates from MR imagery
User: shrey1216
prostate-cancer,Developing the framework to model disease progression in prostate cancer mouse models
User: silvanoross
prostate-cancer,This repository is dedicated to raising awareness about prostate cancer through the prediction of prostate cancer and the explanation of the model's prediction using OmniXAI Explainers.
User: siraug
prostate-cancer,Prostate Cancer Awareness Site
User: snufkindle
prostate-cancer,Exploratory project to study some instances of application of Deep Learning in biostatistics
User: sprstat
prostate-cancer,Jupyter Notebook as course project for AGDPM 2023 at Technical University of Sofia
User: stanislavstoyanov99
prostate-cancer,prostateredcap: R package and workflow for a reproducible clinical-genomic database of prostate cancer
User: stopsack
Home Page: https://stopsack.github.io/prostateredcap
prostate-cancer,PAM50 classifier for Prostate Cancer in Python
User: swiri021
prostate-cancer,PCTA web application by Django
User: swiri021
prostate-cancer,Keras/Tensorflow implementation of 3D pix2pix for automating seed planning for prostate brachytherapy
User: tajwarabraraleef
prostate-cancer,Keras/Tensorflow implementation for co-generation and segmentation of surgical instruments using unlabelled robot-assisted surgery data.
User: tajwarabraraleef
prostate-cancer,Keras/Tensorflow implementation of TP-GAN (end-to-end automatic approach for treatment planning in low-dose-rate prostate brachytherapy)
User: tajwarabraraleef
prostate-cancer,Framework for detecting needle deflection and registering TTMB biopsy cores
User: tajwarabraraleef
prostate-cancer,prostatecancer.ai is an AI-based, zero-footprint medical image viewer that can identify clinically significant prostate cancer.
Organization: tesseract-mi
Home Page: http://prostatecancer.ai/
prostate-cancer,Soft Computing Project by Shoffiyah (140810160057) and Patricia (140810160065).
User: trianne24
prostate-cancer,Using diffusion basis spectrum imaging (DBSI) and multi layer perceptron (MLP) for prostate cancer (PCa) prediction.
User: xmuyzz
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