We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conquer approach in which each heuristic solves a unique subset of the instance...
Computational intelligence and neuroscience
31379935
In this paper, a hybrid deep neural network scheduler (HDNNS) is proposed to solve job-shop scheduling problems (JSSPs). In order to mine the state information of schedule processing, a job-shop scheduling problem is divided into several classificati...
IEEE/ACM transactions on computational biology and bioinformatics
30716047
Single machine total weighted tardiness problem (SMTWTP) is one of the fundamental combinatorial optimization problems. The problem consists of a set of independent jobs with distinct processing times, weights, and due dates to be scheduled on a sing...
PURPOSE: To study whether ICU staffing features are associated with improved hospital mortality, ICU length of stay (LOS) and duration of mechanical ventilation (MV) using cluster analysis directed by machine learning.
International journal of computer assisted radiology and surgery
32242298
PURPOSE: Autonomously self-navigating clinical assistance systems (ASCAS) seem highly promising for improving clinical workflows. There is great potential for easing staff workload and improving overall efficiency by reducing monotonous and physicall...
Studies in health technology and informatics
39049259
The effective management of human resources in nursing fundamental to ensuring high-quality care. The necessary staffing levels can beis derived from the nursing-related health status. Our approach is based on the use of artificial intelligence (AI) ...
Studies in health technology and informatics
39176968
The effective management of human resources in nursing is fundamental to ensuring high-quality care. The necessary staffing levels can be derived from the nursing-related health status. Our approach is based on the use of artificial intelligence (AI)...
Journal of evaluation in clinical practice
39835767
OBJECTIVE: This study aims to assess the performance of machine learning (ML) techniques in optimising nurse staffing and evaluating the appropriateness of nursing care delivery models in hospital wards. The primary outcome measures include the adequ...
BACKGROUND: Machine learning (ML) models can enhance patient-nurse assignments in healthcare organisations by learning from real data and identifying key capabilities. Nurses must develop innovative ideas for adapting to the dynamic environment, mana...