About

Medical Diagnosis is the process of identifying the disease a patient is affected by, based on the assessment of specific risk factors, signs, symptoms and results of exams.

Source: A probabilistic network for the diagnosis of acute cardiopulmonary diseases

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Datasets

Greatest papers with code

PaddleSeg: A High-Efficient Development Toolkit for Image Segmentation

15 Jan 2021PaddlePaddle/PaddleSeg

The toolkit aims to help both developers and researchers in the whole process of designing segmentation models, training models, optimizing performance and inference speed, and deploying models.

AUTONOMOUS DRIVING HUMAN PART SEGMENTATION MEDICAL DIAGNOSIS SEMANTIC SEGMENTATION

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

DropConnect Is Effective in Modeling Uncertainty of Bayesian Deep Networks

7 Jun 2019ElementAI/baal

In this paper, we develop a theoretical framework to approximate Bayesian inference for DNNs by imposing a Bernoulli distribution on the model weights.

AUTONOMOUS DRIVING BAYESIAN INFERENCE MEDICAL DIAGNOSIS SEMANTIC SEGMENTATION

Multi-layer Representation Learning for Medical Concepts

17 Feb 2016mp2893/med2vec

Learning efficient representations for concepts has been proven to be an important basis for many applications such as machine translation or document classification.

DOCUMENT CLASSIFICATION MACHINE TRANSLATION MEDICAL DIAGNOSIS REPRESENTATION LEARNING

A Benchmark of Medical Out of Distribution Detection

8 Jul 2020mlmed/chester-xray

However it is unclear which OoDD method should be used in practice.

MEDICAL DIAGNOSIS OUT-OF-DISTRIBUTION DETECTION

High-Resolution Breast Cancer Screening with Multi-View Deep Convolutional Neural Networks

21 Mar 2017nyukat/BIRADS_classifier

In our work, we propose to use a multi-view deep convolutional neural network that handles a set of high-resolution medical images.

BREAST CANCER DETECTION MEDICAL DIAGNOSIS

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