Infectious Disease

Deep learning-based classification for lung opacities in chest x-ray radiographs through batch control and sensitivity regulation.

In this study, we implemented a system to classify lung opacities from frontal chest x-ray radiographs. We also proposed a training method to address the class imbalance problem presented in the dataset. We participated in the Radiological Society of America (RSNA) 2018 Pneumonia Detection Challenge and used the datasets provided by the RSNA for further research. Using convolutional neural network...

Automatic deep learning-based consolidation/collapse classification in lung ultrasound images for COVID-19 induced pneumonia.

Our automated deep learning-based approach identifies consolidation/collapse in LUS images to aid in the identification of late stages of COVID-19 induced pneumonia, where consolidation/collapse is one of the possible associated pathologies. A common challenge in training such models is that annotating each frame of an ultrasound video requires high labelling effort. This effort in practice become...

Deep learning in acute vertigo diagnosis.

Recent advances in artificial intelligence are transforming healthcare and there are increasing efforts to apply these breakthroughs to the diagnosis ...

Light-driven microrobots: capture and transport of bacteria and microparticles in a fluid medium.

The design of simple microrobotic systems with capabilities to address various applications like cargo transportation, as well as biological sample ca...

Forecasting Weekly Dengue Cases by Integrating Google Earth Engine-Based Risk Predictor Generation and Google Colab-Based Deep Learning Modeling in Fortaleza and the Federal District, Brazil.

Efficient and accurate dengue risk prediction is an important basis for dengue prevention and control, which faces challenges, such as downloading and...

Classification and Detection of COVID-19 and Other Chest-Related Diseases Using Transfer Learning.

COVID-19 has infected millions of people worldwide over the past few years. The main technique used for COVID-19 detection is reverse transcription, w...

Automated system for classification of COVID-19 infection from lung CT images based on machine learning and deep learning techniques.

The objectives of our proposed study were as follows: First objective is to segment the CT images using a k-means clustering algorithm for extracting ...

Nondestructive and multiplex differentiation of pathogenic microorganisms from spoilage microflora on seafood using paper chromogenic array and neural network.

Non-destructive detection of human foodborne pathogens is critical to ensuring food safety and public health. Here, we report a new method using a pap...

Advances in Deep Learning for Tuberculosis Screening using Chest X-rays: The Last 5 Years Review.

There has been an explosive growth in research over the last decade exploring machine learning techniques for analyzing chest X-ray (CXR) images for s...

Computer-aided diagnostic for classifying chest X-ray images using deep ensemble learning.

BACKGROUND: Nowadays doctors and radiologists are overwhelmed with a huge amount of work. This led to the effort to design different Computer-Aided Di...

Deep Transfer Learning for COVID-19 Detection and Lesion Recognition Using Chest CT Images.

Starting from December 2019, the global pandemic of coronavirus disease 2019 (COVID-19) is continuously expanding and has caused several millions of d...

LCSB-inception: Reliable and effective light-chroma separated branches for Covid-19 detection from chest X-ray images.

According to the World Health Organization, an estimate of more than five million infections and 355,000 deaths have been recorded worldwide since the...

Deep learning of longitudinal chest X-ray and clinical variables predicts duration on ventilator and mortality in COVID-19 patients.

OBJECTIVES: To use deep learning of serial portable chest X-ray (pCXR) and clinical variables to predict mortality and duration on invasive mechanical...

A deep learning approach to real-time HIV outbreak detection using genetic data.

Pathogen genomic sequence data are increasingly made available for epidemiological monitoring. A main interest is to identify and assess the potential...

De novo design of anti-tuberculosis agents using a structure-based deep learning method.

Mycobacterium tuberculosis (Mtb) is a pathogen of major concern due to its ability to withstand both first- and second-line antibiotics, leading to dr...

Analysis of Characteristic Factors of Nursing Safety Incidents in ENT Surgery by Deep Learning-Based Medical Data Association Rules Method.

It is of great significance to explore the characteristic factors of postoperative nursing safety events in patients with otolaryngology surgery and t...

Artificial Intelligence and Deep Learning Assisted Rapid Diagnosis of COVID-19 from Chest Radiographical Images: A Survey.

Artificial Intelligence (AI) has been applied successfully in many real-life domains for solving complex problems. With the invention of Machine Learn...

Label-free bacteria identification for clinical applications.

We have developed a system for bacteria identification based on absorption spectroscopy in the mid-infrared spectral range. The data collected are ana...

Phenotyping in clinical text with unsupervised numerical reasoning for patient stratification.

Phenotypic information of patients, as expressed in clinical text, is important in many clinical applications such as identifying patients at risk of ...

Human Monkeypox Classification from Skin Lesion Images with Deep Pre-trained Network using Mobile Application.

Recently, human monkeypox outbreaks have been reported in many countries. According to the reports and studies, quick determination and isolation of i...