Pneumonia is the leading cause of death among children around the world. According to WHO, a total of 740,180 lives under the age of five were lost due to pneumonia in 2019. Lung ultrasound (LUS) has been shown to be particularly useful for ...

• Fusing pediatric LUS data encodings for video-level classification for presence/absence of consolidations due to pneumonia.
• Analysis of LUS data encodings, separately and fused, and their contribution to accurate video-level ...

Pneumonia is a severe disease in children and adults caused by lung infection. It is also the major cause of death in young children. Early diagnosis of pneumonia is essential as it can be life-threatening if not treated at the right time. In this paper,...

Pneumonia and COVID-19 are respiratory illnesses, the last caused by the severe acute respiratory syndrome virus, coronavirus 2 (SARS-CoV-2). Traditional detection processes can be slow, prone to errors, and laborious, leading to potential human ...

Today, with the expansion of technology and new architectures of deep learning, the accuracy of artificial intelligence methods in diagnosing diseases has increased. On the other hand, with the spread of new pandemic diseases such as Covid-19, ...

The purpose of this survey is to provide a comprehensive review of the most recent publications on lung disease classification from chest X-ray images using deep learning algorithms. Methods: This research aims to present several common chest ...

A lung infection is usually the cause of pneumonia, a common medical condition. It irritates the lungs’ tissues and reduces their functionality. The severity of pneumonia can vary from a minor illness to a serious one. Identifying the exact infection ...

In recent years, deep learning has experienced rapid advancement and significant success, particularly in the field of medical image analysis. However, emerging studies have highlighted a critical vulnerability: deep learning systems are susceptible to ...

Chest X-ray images (CXR) can convey a great deal about a patient’s condition; hence, the standard chest radiograph should be reconsidered. Interpretation of radiographs is challenging and requires skilled people to determine lung disease without ...

Diagnosing lung inflammation, particularly pneumonia, is of paramount importance for effectively treating and managing the disease. Pneumonia is a common respiratory infection caused by bacteria, viruses, or fungi and can indiscriminately affect ...

Lung diseases are one of the most common diseases around the world. The risk of these diseases are more in under-developed and developing countries, where millions of people are battling with poverty and living in polluted air. Chest X-Ray images ...

The data hungry nature of neural networks acts as a barrier to their application in data-scarce scenarios like medical domain. Few-shot learning has attracted much interest recently in handling small-scale datasets. Along with the need to handle ...

• The proposed method attains high classification accuracy with visual explanations.
• Our work using few-shot model with explantions shows its potential on small data.
• Our method can be applied to other medical imaging datasets in the ...

• Extending the classic validation workflow to deal with imperfect ground truth by using Bayesian latent class models (BLCA) to estimate accuracy.
• Extending the classic validation workflow to assess the applicability and acceptance of a ...

Community-acquired Pneumonia (CAP) is a common childhood infectious disease. Deep learning models show promise in X-ray interpretation and diagnosis, but their validation should be extended due to limitations in the current validation ...

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Pneumonia is a severe respiratory infection that can cause life-threatening complications if left untreated. Although an early and accurate diagnosis is essential for successful treatment, conventional techniques of diagnosis can be expensive and time-...

Pneumonia is an infection that inflames the air sacs in lungs and is one of the prime causes of deaths under the age of five, all over the world. Moreover, sometimes it became quite difficult to detect and diagnose pneumonia by just looking at the ...

Although non-interpretable (black-box) deep learning models are well known for their accuracy, interpretable deep learning models should be used for high stake decisions, such as: healthcare. In this paper, we present a novel technique of ...

• Comb-ProtoPNet introduces a novel technique to form ensemble algorithms.
• Comb-ProtoPNet combines the algorithms themselves instead of combining their outputs.
• Comb-ProtoPNet uses prototypes with rectangular and square spatial ...

Numerous epidemic lung diseases such as COVID-19, tuberculosis (TB), and pneumonia have spread over the world, killing millions of people. Medical specialists have experienced challenges in correctly identifying these diseases due to ...

Unsupervised anomaly detection (UAD) aims to find anomalous images by optimising a detector using a training set that contains only normal images. UAD approaches can be based on reconstruction methods, self-supervised approaches, and Imagenet pre-...

Around the world, lung disease is a prevalent cause of death and illness. In this article, we propose a lung disease detection system for the automated identification of critical lung diseases: 1. Tuberculosis 2. Regular Pneumonia 3. COVID ...

COVID-19 has been a devastating pandemic, causing serious and sometimes irreparable damages to body organs. The sooner the existence of this virus in the body is recognized, the more effective the treatments are. This early detection can break the ...

Pneumonia disease is caused by viruses and bacteria which affect one or both lungs. It is the most dangerous disease that causes huge cancer death worldwide. Early detection of Pneumonia is the only way to improve a patient’s chance for survival. ...