AIMC Topic: COVID-19

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Simplified Transfer Learning for Chest Radiography Models Using Less Data.

Radiology
Background Developing deep learning models for radiology requires large data sets and substantial computational resources. Data set size limitations can be further exacerbated by distribution shifts, such as rapid changes in patient populations and s...

An efficient deep learning-based framework for tuberculosis detection using chest X-ray images.

Tuberculosis (Edinburgh, Scotland)
Early diagnosis of tuberculosis (TB) is an essential and challenging task to prevent disease, decrease mortality risk, and stop transmission to other people. The chest X-ray (CXR) is the top choice for lung disease screening in clinics because it is ...

Argument mining as rapid screening tool of COVID-19 literature quality: Preliminary evidence.

Frontiers in public health
BACKGROUND: The COVID-19 pandemic prompted the scientific community to share timely evidence, also in the form of pre-printed papers, not peer reviewed yet.

InjectMeAI-Software Module of an Autonomous Injection Humanoid.

Sensors (Basel, Switzerland)
The recent pandemic outbreak proved social distancing effective in helping curb the spread of SARS-CoV-2 variants along with the wearing of masks and hand gloves in hospitals and assisted living environments. Health delivery personnel having undergon...

Classification of COVID-19 from tuberculosis and pneumonia using deep learning techniques.

Medical & biological engineering & computing
Deep learning provides the healthcare industry with the ability to analyse data at exceptional speeds without compromising on accuracy. These techniques are applicable to healthcare domain for accurate and timely prediction. Convolutional neural netw...

COVID-19 Classification from Chest X-Ray Images: A Framework of Deep Explainable Artificial Intelligence.

Computational intelligence and neuroscience
COVID-19 detection and classification using chest X-ray images is a current hot research topic based on the important application known as medical image analysis. To halt the spread of COVID-19, it is critical to identify the infection as soon as pos...

Feature-level ensemble approach for COVID-19 detection using chest X-ray images.

PloS one
Severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), also known as the coronavirus disease 2019 (COVID-19), has threatened many human beings around the world and capsized economies at unprecedented magnitudes. Therefore, the detection of thi...

Mortality Prediction Analysis among COVID-19 Inpatients Using Clinical Variables and Deep Learning Chest Radiography Imaging Features.

Tomography (Ann Arbor, Mich.)
The emergence of the COVID-19 pandemic over a relatively brief interval illustrates the need for rapid data-driven approaches to facilitate clinical decision making. We examined a machine learning process to predict inpatient mortality among COVID-19...

Non-iterative learning machine for identifying CoViD19 using chest X-ray images.

Scientific reports
CoViD19 is a novel disease which has created panic worldwide by infecting millions of people around the world. The last significant variant of this virus, called as omicron, contributed to majority of cases in the third wave across globe. Though less...

Exploring COVID-19-Related Stressors: Topic Modeling Study.

Journal of medical Internet research
BACKGROUND: The COVID-19 pandemic has affected the lives of people globally for over 2 years. Changes in lifestyles due to the pandemic may cause psychosocial stressors for individuals and could lead to mental health problems. To provide high-quality...