Steroids

A machine learning approach identifies 5-ASA and ulcerative colitis as being linked with higher COVID-19 mortality in patients with IBD.

Inflammatory bowel diseases (IBD), namely Crohn's disease (CD) and ulcerative colitis (UC) are chronic inflammation within the gastrointestinal tract. IBD patient conditions and treatments, such as with immunosuppressants, may result in a higher risk of viral and bacterial infection and more severe outcomes of infections. The effect of the clinical and demographic factors on the prognosis of COVID...

Machine learning using clinical data at baseline predicts the efficacy of vedolizumab at week 22 in patients with ulcerative colitis.

Predicting the response of patients with ulcerative colitis (UC) to a biologic such as vedolizumab (VDZ) before administration is an unmet need for optimizing individual patient treatment. We hypothesized that the machine-learning approach with daily clinical information can be a new, promising strategy for developing a drug-efficacy prediction tool. Random forest with grid search and cross-valida...

Robotic Assay for Drought (RoAD): an automated phenotyping system for brassinosteroid and drought responses.

Brassinosteroids (BRs) are a group of plant steroid hormones involved in regulating growth, development, and stress responses. Many components of the ...

Development of Machine Learning Models for Prediction of Osteoporosis from Clinical Health Examination Data.

Osteoporosis is treatable but often overlooked in clinical practice. We aimed to construct prediction models with machine learning algorithms to serve...

An Unbiased Machine Learning Exploration Reveals Gene Sets Predictive of Allograft Tolerance After Kidney Transplantation.

Efforts at finding potential biomarkers of tolerance after kidney transplantation have been hindered by limited sample size, as well as the complicate...

Bone mineral density response prediction following osteoporosis treatment using machine learning to aid personalized therapy.

Osteoporosis is a global health problem for ageing populations. The goals of osteoporosis treatment are to improve bone mineral density (BMD) and prev...

Ultrasensitive biosensors based on waveguide-coupled long-range surface plasmon resonance (WC-LRSPR) for enhanced fluorescence spectroscopy.

We investigated the coupling phenomenon between plasmonic resonance and waveguide modes through theoretical and experimental parametric analyses on th...

Analysis of cognitive impairment in schizophrenia based on machine learning: Interaction between psychological stress and immune system.

The interaction between psychological stress and immune system may be associated with the cognitive impairment of schizophrenia. To employ machine lea...

Augmenting the Transplant Team With Artificial Intelligence: Toward Meaningful AI Use in Solid Organ Transplant.

Advances in systems immunology, such as new biomarkers, offer the potential for highly personalized immunosuppression regimens that could improve pati...

Robot-assisted donor hysterectomy in uterus transplantation - a modality to increase reproducibility.

Uterus transplantation is a non-lifesaving vascularized composite allotransplantation procedure requiring immunosuppression until removal of the graft...

Prediction model for the risk of osteoporosis incorporating factors of disease history and living habits in physical examination of population in Chongqing, Southwest China: based on artificial neural network.

BACKGROUND: Osteoporosis is a gradually recognized health problem with risks related to disease history and living habits. This study aims to establis...

Using Graph Representation Learning to Predict Salivary Cortisol Levels in Pancreatic Cancer Patients.

Cortisol is a glucocorticoid hormone that is critical to immune system functioning. Studies show that prolonged exposure to high levels of cortisol ca...

A deep learning system for automated, multi-modality 2D segmentation of vertebral bodies and intervertebral discs.

PURPOSE: Fractures in vertebral bodies are among the most common complications of osteoporosis and other bone diseases. However, studies that aim to p...

Mycophenolic Acid Exposure Prediction Using Machine Learning.

Therapeutic drug monitoring of mycophenolic acid (MPA) based on area under the curve (AUC) is well-established and machine learning (ML) approaches co...

SteroidXtract: Deep Learning-Based Pattern Recognition Enables Comprehensive and Rapid Extraction of Steroid-Like Metabolic Features for Automated Biology-Driven Metabolomics.

Despite the vast amount of metabolic information that can be captured in untargeted metabolomics, many biological applications are looking for a biolo...

Deep convolutional neural network: a novel approach for the detection of Aspergillus fungi via stereomicroscopy.

Fungi of the genus Aspergillus are ubiquitously distributed in nature, and some cause invasive aspergillosis (IA) infections in immunosuppressed indiv...

Machine Learning as a Precision-Medicine Approach to Prescribing COVID-19 Pharmacotherapy with Remdesivir or Corticosteroids.

PURPOSE: Coronavirus disease-2019 (COVID-19) continues to be a global threat and remains a significant cause of hospitalizations. Recent clinical guid...

Machine learning analysis of gene expression profile reveals a novel diagnostic signature for osteoporosis.

BACKGROUND: Osteoporosis (OP) is increasingly prevalent with the aging of the world population. It is urgent to identify efficient diagnostic signatur...

Prediction of femoral osteoporosis using machine-learning analysis with radiomics features and abdomen-pelvic CT: A retrospective single center preliminary study.

BACKGROUND: Osteoporosis has increased and developed into a serious public health concern worldwide. Despite the high prevalence, osteoporosis is sile...

Application Prospect of Artificial Intelligence in Rehabilitation and Management of Myasthenia Gravis.

Myasthenia gravis (MG) is a chronic autoimmune disease of the nervous system, which is still incurable. In recent years, with the progress of immunosu...