BACKGROUND: To predict mycophenolic acid (MPA) exposure in renal transplant recipients using a deep learning model based on a convolutional neural network with bilateral long short-term memory and attention methods.
INTRODUCTION: Mycophenolate mofetil and its active metabolite mycophenolic acid are routinely used as immunosuppressant drugs in solid organ transplantation in a fixed daily dose regimen in association with cyclosporine, tacrolimus and steroids. Ther...
European review for medical and pharmacological sciences
Nov 1, 2020
Researchers have found many similarities between the 2003 severe acute respiratory syndrome (SARS) virus and SARS-CoV-19 through existing data that reveal the SARS's cause. Artificial intelligence (AI) learning models can be created to predict drug s...
Current opinion in organ transplantation
Aug 1, 2020
PURPOSE OF REVIEW: The success of organ transplant is determined by number of demographic, clinical, immunological and genetic variables. Artificial intelligence tools, such as artificial neural networks (ANNs) or classification and regression trees ...
BACKGROUND: The gut-selective nature of vedolizumab has raised questions regarding increased joint pain or arthralgia with its use in inflammatory bowel disease (IBD) patients. As arthralgias are seldom coded and thus difficult to study, few studies ...
BACKGROUND: Immunosuppressant Bayesian dose adjustment (ISBA) is an online expert system, routinely used by approximately 140 transplantation centers in the world for the dose adjustment of immunosuppressive drugs in transplant patients. This system ...
BACKGROUND: Inflammatory bowel disease (IBD) is a chronic disease characterized by unpredictable episodes of flares and periods of remission. Tools that accurately predict disease course would substantially aid therapeutic decision-making. This study...
OBJECTIVES: To determine the possible association of serum 25-hydroxyvitamin D (25OHD) levels with disease activity and respiratory infection in granulomatosis with polyangiitis patients during two different periods: winter/spring and summer/autumn.
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