International journal of medical informatics
Jun 13, 2024
BACKGROUND: The surge in emergency head CT imaging and artificial intelligence (AI) advancements, especially deep learning (DL) and convolutional neural networks (CNN), have accelerated the development of computer-aided diagnosis (CADx) for emergency...
Liver resection is one of the best treatments for small hepatocellular carcinoma (HCC), but post-resection recurrence is frequent. Biotherapies have emerged as an efficient adjuvant treatment, making the identification of patients at high risk of rec...
Endometrial cancer is the fourth most common cancer in women in the United States, with a lifetime risk of approximately 2.8%. Precise histologic evaluation and molecular classification of endometrial cancer are important for effective patient manage...
OBJECTIVE: To develop and validate natural language processing-driven artificial intelligence (AI) models for the diagnosis of lumbar disc herniation (LDH) with L5 and S1 radiculopathy using electronic health records (EHRs).
Over the past few years, the widespread outbreak of COVID-19 has caused the death of millions of people worldwide. Early diagnosis of the virus is essential to control its spread and provide timely treatment. Artificial intelligence methods are often...
The value of machine learning capacity in maternal health, and in particular prediction of preeclampsia will only be realised when there are high quality clinical data provided, representative populations included, different health systems and models...
BACKGROUND: Machine learning (ML) is increasingly used to predict the prognosis of numerous diseases. This retrospective analysis aimed to develop a prediction model using ML algorithms and to identify predictors associated with the recurrence of hal...
Computers and applications of computers into our world have changed dramatically during the past five decades, from early days of minimal central processing unit capacity, limited memory and without advantage of global networking. In this article, th...
International journal of neural systems
Jun 13, 2024
Domain adaptation is a subfield of statistical learning theory that takes into account the shift between the distribution of training and test data, typically known as source and target domains, respectively. In this context, this paper presents an i...
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