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Found 9 papers, 6 papers with code
Publicly available datasets of breast histopathology H&E whole-slide images: A scoping review
In this scoping review, we identified the publicly available datasets of breast H&E stained whole-slide images (WSI) that can be used to develop deep learning algorithms.
What is the state of the art? Accounting for multiplicity in machine learning benchmark performance
In this article, we provide a probability distribution for the case of multiple classifiers so that known analyses methods can be engaged and a better SOTA estimate can be provided.
A Pragmatic Machine Learning Approach to Quantify Tumor Infiltrating Lymphocytes in Whole Slide Images
Our approach is to transfer an open source machine learning method for segmentation and classification of nuclei in H&E slides trained on public data to TIL quantification without manual labeling of our data.
Instance Segmentation of Microscopic Foraminifera
The model achieves a (COCO-style) average precision of $0. 78 \pm 0. 00$ on the classification and detection task, and $0. 80 \pm 0. 00$ on the segmentation task.
Reproduction study using public data of: Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs
We have attempted to reproduce the results in Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs, published in JAMA 2016; 316(22), using publicly available data sets.
Ranked #2 on
Diabetic Retinopathy Grading
on Kaggle EyePACS
Replication study: Development and validation of deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs
We have attempted to replicate the main method in 'Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs' published in JAMA 2016; 316(22).
Diabetic Retinopathy Detection
Medical Image Segmentation
+1
A bag-to-class divergence approach to multiple-instance learning
A different viewpoint is that the instances are realisations of random vectors with corresponding probability distribution, and that a bag is the distribution, not the realisations.
Comparison of computer systems and ranking criteria for automatic melanoma detection in dermoscopic images
A small set of similar classification algorithms are used to investigate the impact of classifier on the diagnostic accuracy.
On Data-Independent Properties for Density-Based Dissimilarity Measures in Hybrid Clustering
In such clustering, a dissimilarity measure plays a crucial role in the hierarchical merging.
