Results 51 to 60 of about 294,873 (258)
Dimension reduction is often used for several procedures of analysis of high dimensional biomedical data-sets such as classification or outlier detection.
Karaj Khosla +3 more
doaj +1 more source
ABSTRACT Pediatric supportive care clinical trials often involve multiple clinically important outcomes, complicating trial interpretation. Hierarchical composite endpoints (HCEs) provide a framework to integrate key outcomes according to clinical importance.
Willem H. Collier +11 more
wiley +1 more source
Kernel-Based Dimension Reduction Method for Time Series Nowcasting
Nowcasts are closely related to big data. Currently, the most popular nowcast model-building approach is to use the factor bridge equation (BE) model or factor mixed data sampling (MIDAS) model, where the factors are extracted from large datasets using ...
Thanh Do Van, Hai Nguyen Minh
doaj +1 more source
ABSTRACT Background Sickle cell disease (SCD) has undergone major changes in the last decades. Its prevalence has been steadily increasing and numerous advances have been made in the management of the disease. However, the effect in real‐life setting of these major changes is unknown, particularly in a Canadian environment. Procedure We aimed to assess
Maude Cigna +16 more
wiley +1 more source
Temperature information has a certain significance in thermal energy systems, especially in gas combustion systems. Generally, measurements and numerical calculations are used to acquire temperature information, but both of these approaches have their ...
Minxin Chen +4 more
doaj +1 more source
ABSTRACT Background Patients with chronic kidney disease undergoing hemodialysis commonly experience reduced physical function, fatigue, poor sleep quality, and impaired health‐related quality of life. Intradialytic exercise has been proposed as a non‐pharmacological strategy to improve these outcomes.
Klebson da Silva Almeida +6 more
wiley +1 more source
Dimension Reduction for Supervised Ordering [PDF]
Ordered lists of objects are widely used as representational forms. Such ordered objects include Web search results and best-seller lists. Techniques for processing such ordinal data are being developed, particularly methods for a supervised ordering task: i.e., learning functions used to sort objects from sample orders. In this article, we propose two
Toshihiro Kamishima, Shotaro Akaho
openaire +1 more source
ABSTRACT Background Chronic micro‐inflammation in patients with end‐stage renal disease (ESRD) is a significant driver of cardiovascular complications and diminished quality of life. While standard hemodialysis (SHD) effectively manages small‐molecule clearance, its ability to remove medium‐to‐large uremic toxins—the primary catalysts of systemic ...
Hongwei Zuo +5 more
wiley +1 more source
Dimension Reduction for Objects Composed of Vector Sets
Dimension reduction and feature selection are fundamental tools for machine learning and data mining. Most existing methods, however, assume that objects are represented by a single vectorial descriptor.
Szemenyei Marton, Vajda Ferenc
doaj +1 more source
ABSTRACT Introduction This final analysis of a multicenter, prospective postmarketing surveillance study evaluated the safety of daprodustat in patients with chronic kidney disease anemia in routine clinical practice in Japan. Methods Patients who initiated daprodustat between September 2020 and July 2022 were registered.
Tadao Akizawa +7 more
wiley +1 more source

