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Comparing machine learning screening approaches using clinical data and cytokine profiles for COVID-19 in resource-limited and resource-abundant settings.
Scientific reports
Jun 28, 2024
Accurate screening of COVID-19 infection status for symptomatic patients is a critical public health task. Although molecular and antigen tests now exist for COVID-19, in resource-limited settings, screening tests are often not available. Furthermore...
Whole-body low-dose computed tomography in patients with newly diagnosed multiple myeloma predicts cytogenetic risk: a deep learning radiogenomics study.
Skeletal radiology
Jun 27, 2024
OBJECTIVE: To develop a whole-body low-dose CT (WBLDCT) deep learning model and determine its accuracy in predicting the presence of cytogenetic abnormalities in multiple myeloma (MM).
Preoperative CT-based radiomics and deep learning model for predicting risk stratification of gastric gastrointestinal stromal tumors.
Medical physics
Jun 27, 2024
BACKGROUND: Gastrointestinal stromal tumors (GISTs) are clinically heterogeneous with various malignant potential in different individuals. It is crucial to explore a reliable method for preoperative risk stratification of gastric GISTs noninvasively...
Radiologists' perceptions on AI integration: An in-depth survey study.
European journal of radiology
Jun 27, 2024
PURPOSE: To assess the perceptions and attitudes of radiologists toward the adoption of artificial intelligence (AI) in clinical practice.
Integrated multi-omics analysis and machine learning developed diagnostic markers and prognostic model based on Efferocytosis-associated signatures for septic cardiomyopathy.
Clinical immunology (Orlando, Fla.)
Jun 27, 2024
Septic cardiomyopathy (SCM) is characterized by an abnormal inflammatory response and increased mortality. The role of efferocytosis in SCM is not well understood. We used integrated multi-omics analysis to explore the clinical and genetic roles of e...
Clinical implementation of artificial-intelligence-assisted detection of breast cancer metastases in sentinel lymph nodes: the CONFIDENT-B single-center, non-randomized clinical trial.
Nature cancer
Jun 27, 2024
Pathologists' assessment of sentinel lymph nodes (SNs) for breast cancer (BC) metastases is a treatment-guiding yet labor-intensive and costly task because of the performance of immunohistochemistry (IHC) in morphologically negative cases. This non-r...
Supervised Machine Learning-Based Models for Predicting Raised Blood Sugar.
International journal of environmental research and public health
Jun 27, 2024
Raised blood sugar (hyperglycemia) is considered a strong indicator of prediabetes or diabetes mellitus. Diabetes mellitus is one of the most common non-communicable diseases (NCDs) affecting the adult population. Recently, the prevalence of diabetes...
Establishment of prediction model for mortality risk of pancreatic cancer: a retrospective study.
BMC medical informatics and decision making
Jun 27, 2024
BACKGROUND AND AIM: Pancreatic cancer possesses a high prevalence and mortality rate among other cancers. Despite the low survival rate of this cancer type, the early prediction of this disease has a crucial role in decreasing the mortality rate and ...
Data-driven prediction of continuous renal replacement therapy survival.
Nature communications
Jun 27, 2024
Continuous renal replacement therapy (CRRT) is a form of dialysis prescribed to severely ill patients who cannot tolerate regular hemodialysis. However, as the patients are typically very ill to begin with, there is always uncertainty whether they wi...
A Comparative Study of a Nomogram and Machine Learning Models in Predicting Early Hematoma Expansion in Hypertensive Intracerebral Hemorrhage.
Academic radiology
Jun 26, 2024
RATIONALE AND OBJECTIVES: Early identification for hematoma expansion can help improve patient outcomes. Presently, there are many methods to predict hematoma expansion. This study compared a variety of models to find a model suitable for clinical pr...
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