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Latest papers with code

$\text{O}^2$PF: Oversampling via Optimum-Path Forest for Breast Cancer Detection

14 Jan 2021Leandropassosjr/o2pf

Breast cancer is among the most deadly diseases, distressing mostly women worldwide.

BREAST CANCER DETECTION

1
14 Jan 2021

Differences between human and machine perception in medical diagnosis

28 Nov 2020nyukat/perception_comparison

We compare the two with respect to their robustness to Gaussian low-pass filtering, performing a subgroup analysis on microcalcifications and soft tissue lesions.

BREAST CANCER DETECTION MEDICAL DIAGNOSIS

20
28 Nov 2020

An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization

13 Feb 2020nyukat/GMIC

In this work, we extend the globally-aware multiple instance classifier, a framework we proposed to address these unique properties of medical images.

BREAST CANCER DETECTION LESION SEGMENTATION MEDICAL DIAGNOSIS WEAKLY-SUPERVISED OBJECT LOCALIZATION

75
13 Feb 2020

Utilizing Automated Breast Cancer Detection to Identify Spatial Distributions of Tumor Infiltrating Lymphocytes in Invasive Breast Cancer

26 May 2019SBU-BMI/quip_cancer_segmentation

Quantitative assessment of Tumor-TIL spatial relationships is increasingly important in both basic science and clinical aspects of breast cancer research.

BREAST CANCER DETECTION

4
26 May 2019

Regression Concept Vectors for Bidirectional Explanations in Histopathology

9 Apr 2019medgift/iMIMIC-RCVs

Explanations for deep neural network predictions in terms of domain-related concepts can be valuable in medical applications, where justifications are important for confidence in the decision-making.

BREAST CANCER DETECTION DECISION MAKING HISTOPATHOLOGICAL IMAGE CLASSIFICATION

14
09 Apr 2019

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening

20 Mar 2019nyukat/breast_cancer_classifier

We present a deep convolutional neural network for breast cancer screening exam classification, trained and evaluated on over 200, 000 exams (over 1, 000, 000 images).

BREAST CANCER DETECTION MEDICAL DIAGNOSIS

624
20 Mar 2019

Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis

2 Feb 2018alexander-rakhlin/ICIAR2018

In this work, we develop the computational approach based on deep convolution neural networks for breast cancer histology image classification.

BREAST CANCER DETECTION GENERAL CLASSIFICATION HISTOPATHOLOGICAL IMAGE CLASSIFICATION IMAGE CLASSIFICATION

165
02 Feb 2018