Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
Abstract Machine learning methods offer great promise for fast and accurate detection and
prognostication of coronavirus disease 2019 (COVID-19) from standard-of-care chest …
prognostication of coronavirus disease 2019 (COVID-19) from standard-of-care chest …
[HTML][HTML] Assessing the utility of ChatGPT throughout the entire clinical workflow: development and usability study
Background Large language model (LLM)–based artificial intelligence chatbots direct the
power of large training data sets toward successive, related tasks as opposed to single-ask …
power of large training data sets toward successive, related tasks as opposed to single-ask …
[HTML][HTML] A systematic review and meta-analysis on ChatGPT and its utilization in medical and dental research
Abstract Background Since its release, ChatGPT has taken the world by storm with its
utilization in various fields of life. This review's main goal was to offer a thorough and fact …
utilization in various fields of life. This review's main goal was to offer a thorough and fact …
Assessing the utility of ChatGPT throughout the entire clinical workflow
IMPORTANCE Large language model (LLM) artificial intelligence (AI) chatbots direct the
power of large training datasets towards successive, related tasks, as opposed to single-ask …
power of large training datasets towards successive, related tasks, as opposed to single-ask …
BS-Net: Learning COVID-19 pneumonia severity on a large chest X-ray dataset
In this work we design an end-to-end deep learning architecture for predicting, on Chest X-
rays images (CXR), a multi-regional score conveying the degree of lung compromise in …
rays images (CXR), a multi-regional score conveying the degree of lung compromise in …
COVID-19 in CXR: From detection and severity scoring to patient disease monitoring
This work estimates the severity of pneumonia in COVID-19 patients and reports the findings
of a longitudinal study of disease progression. It presents a deep learning model for …
of a longitudinal study of disease progression. It presents a deep learning model for …
Developing medical imaging AI for emerging infectious diseases
Advances in artificial intelligence (AI) and computer vision hold great promise for assisting
medical staff, optimizing healthcare workflow, and improving patient outcomes. The COVID …
medical staff, optimizing healthcare workflow, and improving patient outcomes. The COVID …
Systematic review of artificial intelligence in acute respiratory distress syndrome for COVID-19 lung patients: a biomedical imaging perspective
SARS-CoV-2 has infected over∼ 165 million people worldwide causing Acute Respiratory
Distress Syndrome (ARDS) and has killed∼ 3.4 million people. Artificial Intelligence (AI) has …
Distress Syndrome (ARDS) and has killed∼ 3.4 million people. Artificial Intelligence (AI) has …
Right ventricular strain is common in intubated COVID-19 patients and does not reflect severity of respiratory illness
Background: Right ventricular (RV) dysfunction is common and associated with worse
outcomes in patients with coronavirus disease 2019 (COVID-19). In non-COVID-19 acute …
outcomes in patients with coronavirus disease 2019 (COVID-19). In non-COVID-19 acute …
Multi-radiologist user study for artificial intelligence-guided grading of COVID-19 lung disease severity on chest radiographs
Rationale and Objectives Radiographic findings of COVID-19 pneumonia can be used for
patient risk stratification; however, radiologist reporting of disease severity is inconsistent on …
patient risk stratification; however, radiologist reporting of disease severity is inconsistent on …