Medical Diagnosis

77 papers with code • 1 benchmarks • 7 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/meta 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.

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.

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.

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening

nyukat/breast_cancer_classifier 20 Mar 2019

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).

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.

UnMask: Adversarial Detection and Defense Through Robust Feature Alignment

safreita1/unmask 21 Feb 2020

UnMask detects such attacks and defends the model by rectifying the misclassification, re-classifying the image based on its robust features.

Automated Model Design and Benchmarking of 3D Deep Learning Models for COVID-19 Detection with Chest CT Scans

marsggbo/CovidNet3D 14 Jan 2021

The experimental results show that our automatically searched models (CovidNet3D) outperform the baseline human-designed models on the three datasets with tens of times smaller model size and higher accuracy.