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COVID-19

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Comparative study of DCNN and image processing based classification of chest X-rays for identification of COVID-19 patients using fine-tuning.

Journal of medical engineering & technology
The conventional detection of COVID-19 by evaluating the CT scan images is tiresome, often experiences high inter-observer variability and uncertainty issues. This work proposes the automatic detection and classification of COVID-19 by analysing the ...

Machine Learning-Based Suicide Risk Prediction Model for Suicidal Trajectory on Social Media Following Suicidal Mentions: Independent Algorithm Validation.

Journal of medical Internet research
BACKGROUND: Previous efforts to apply machine learning-based natural language processing to longitudinally collected social media data have shown promise in predicting suicide risk.

Using machine learning for personalized prediction of longitudinal coronavirus disease 2019 vaccine responses in transplant recipients.

American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
The coronavirus disease 2019 pandemic has underscored the importance of vaccines, especially for immunocompromised populations like solid organ transplant recipients, who often have weaker immune responses. The purpose of this study was to compare de...

Prediction of prolonged mechanical ventilation in the intensive care unit via machine learning: a COVID-19 perspective.

Scientific reports
Early recognition of risk factors for prolonged mechanical ventilation (PMV) could allow for early clinical interventions, prevention of secondary complications such as nosocomial infections, and effective triage of hospital resources. This study tes...

Leveraging deep transfer learning and explainable AI for accurate COVID-19 diagnosis: Insights from a multi-national chest CT scan study.

Computers in biology and medicine
The COVID-19 pandemic has emerged as a global health crisis, impacting millions worldwide. Although chest computed tomography (CT) scan images are pivotal in diagnosing COVID-19, their manual interpretation by radiologists is time-consuming and poten...

Predictive analysis of COVID-19 occurrence and vaccination impacts across the 50 US states.

Computers in biology and medicine
OBJECTIVE: This study aimed to outline a machine learning model to assess the effectiveness of vaccination in COVID-19 confirmed cases and fatalities. The proposed model was evaluated using external validation to ensure optimal protection of vaccinat...

Artificial intelligence enabled smart mask for speech recognition for future hearing devices.

Scientific reports
In recent years, Lip-reading has emerged as a significant research challenge. The aim is to recognise speech by analysing Lip movements. The majority of Lip-reading technologies are based on cameras and wearable devices. However, these technologies h...

Reflections From the Pandemic: Is Connectivism the Panacea for Clinicians?

Journal of medical Internet research
The COVID-19 pandemic and the recent increased interest in generative artificial intelligence (GenAI) highlight the need for interprofessional communities' collaboration to find solutions to complex problems. A personal narrative experience of one of...

Integrating graph and reinforcement learning for vaccination strategies in complex networks.

Scientific reports
Pandemics like COVID-19 have a huge impact on human society and the global economy. Vaccines are effective in the fight against these pandemics but often in limited supplies, particularly in the early stages. Thus, it is imperative to distribute such...

Accurate Lung Nodule Segmentation With Detailed Representation Transfer and Soft Mask Supervision.

IEEE transactions on neural networks and learning systems
Accurate lung lesion segmentation from computed tomography (CT) images is crucial to the analysis and diagnosis of lung diseases, such as COVID-19 and lung cancer. However, the smallness and variety of lung nodules and the lack of high-quality labeli...