Results 81 to 90 of about 14,811,766 (247)
Optimization based machine learning algorithms for software reliability growth models
Software reliability is a critical factor for system performance and safety, especially in defense industries, where operational failures can have severe consequences.
Myeongguen Shin +4 more
doaj
Predictive Value of Composite Inflammatory Markers for Stroke Prognosis: A Prospective Cohort Study
ABSTRACT Background Novel composite inflammatory markers' role in stroke prognosis is understudied, and the best predictor is unclear, requiring further exploration. Objectives This study aimed to systematically evaluate the associations of 6 novel composite inflammatory markers on stroke prognosis.
Bing Wu +7 more
wiley +1 more source
ABSTRACT Objective The prognosis of glioblastoma (GBM) remains highly unfavorable, largely due to high tumor heterogeneity and an immunosuppressive microenvironment. However, the functional role of PANoptosis in this context is poorly understood. Methods Patients were stratified via K‐means clustering. A risk score model was constructed using prognosis‐
Langfei Tian +6 more
wiley +1 more source
A Modified Genetic Algorithm for Parameter Estimation of Software Reliability Growth Models
[[abstract]]©2008 IEEE-In this paper, we propose a modified genetic algorithm (MGA) with calibrating fitness functions, weighted bit mutation, and rebuilding mechanism for the parameter estimation of software reliability growth models (SRGMs). An example
Chao-Jung Hsu;Chin-Yu Huang;Tsan-Yuan Chen
core +1 more source
ABSTRACT Objective To evaluate the diagnostic accuracy of glial fibrillary acidic protein (GFAP) measured in dried plasma spots versus conventional plasma‐ and serum‐GFAP testing for assessment of disease severity in aquaporin‐4 immunoglobulin G–positive neuromyelitis optica spectrum disorder (AQP4‐IgG+ NMOSD).
Felix Wohlrab +19 more
wiley +1 more source
This study presents a Software Reliability Growth Model (SRGM) that incorporates imperfect debugging and employs Bayesian analysis to optimize the timing of software releases.
Chih-Chiang Fang, Liping Ma, Wenfeng Kuo
doaj +1 more source
Objective We aimed to construct and evaluate the first laboratory‐based frailty index (FI‐Lab) for predicting adverse outcomes in systemic lupus erythematosus (SLE) and to compare its predictive ability to that of an existing clinical FI. Methods We used data from a single‐center prospective cohort of adult patients with SLE whose baseline visit ...
Grace Burns +2 more
wiley +1 more source
Objective This study aimed to investigate hand function trajectories over five years in primary hand osteoarthritis (OA). Additionally, determinants of baseline and longitudinal hand function were assessed. Methods A total of 538 patients with both baseline and five‐year study visits were analyzed.
Annemiek V. E. M. Olde Meule +4 more
wiley +1 more source
DNN-based Software Reliability Model for Fault Prediction and Optimal Release Time Determination [PDF]
The accurate prediction of both detected and corrected faults is crucial for enhancing software reliability and determining optimal release times. Traditional Software Reliability Growth Models (SRGMs) often focus on either fault detection or correction,
Shikha Dwivedi +2 more
doaj +1 more source
Objective To evaluate how modifiable psychosocial factors and fatigue relate to physical functioning in patients with systemic lupus erythematosus (SLE). Methods In this cross‐sectional study of two demographically distinct cohorts (Approaches to Positive, Patient‐Centered Experiences of Aging with Lupus [APPEAL] and California Lupus Epidemiology Study
Mrinalini Dey +8 more
wiley +1 more source

