Medical Diagnosis

213 papers with code • 2 benchmarks • 21 datasets

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

Most implemented papers

BreastScreening: On the Use of Multi-Modality in Medical Imaging Diagnosis

MIMBCD-UI/prototype-multi-modality 7 Apr 2020

This paper describes the field research, design and comparative deployment of a multimodal medical imaging user interface for breast screening.

Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat at Label Shift Adaptation

kundajelab/abstention 21 Jan 2019

Label shift refers to the phenomenon where the prior class probability p(y) changes between the training and test distributions, while the conditional probability p(x|y) stays fixed.

DropConnect Is Effective in Modeling Uncertainty of Bayesian Deep Networks

ElementAI/baal 7 Jun 2019

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

D-UNet: a dimension-fusion U shape network for chronic stroke lesion segmentation

SZUHvern/D-UNet 14 Aug 2019

This function adds a weighted focal coefficient and combines two traditional loss functions.

A Benchmark of Medical Out of Distribution Detection

caotians1/OD-test-master 8 Jul 2020

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

DP-MDM: Detail-Preserving MR Reconstruction via Multiple Diffusion Models

yqx7150/dp-mdm 9 May 2024

Moreover, virtual binary modal masks are utilized to refine the range of values in k-space data through highly adaptive center windows, which allows the model to focus its attention more efficiently.

Multi-layer Representation Learning for Medical Concepts

mp2893/med2vec 17 Feb 2016

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

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

nyukat/BIRADS_classifier 21 Mar 2017

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

TCAV: Relative concept importance testing with Linear Concept Activation Vectors

tensorflow/tcav ICLR 2018

In particular, this framework enables non-machine learning experts to express concepts of interests and test hypotheses using examples (e. g., a set of pictures that illustrate the concept).

Detecting and Correcting for Label Shift with Black Box Predictors

levon003/cscw-caringbridge-interaction-network ICML 2018

Faced with distribution shift between training and test set, we wish to detect and quantify the shift, and to correct our classifiers without test set labels.