Introduction Efficient preventive management of acute exacerbation of chronic obstructive pulmonary disease (COPD) is ...

Abstract: Considering the diversity of uniform distribution for the solutions of multi-objective optimization problems, we propose the multi-objective genetic algorithm based on fitting (MOGA/F) and ...

This paper presents a robust multi-objective optimization approach—the multi-objective starfish optimization algorithm (MOSFOA)—designed to address complex challenges in engineering design and optimal ...

Abstract: Passenger flow recognition is the basis of railway passenger terminal station and railway operation department for daily management, it has an important significance for the adjustment of ...

Library Evolutionary Algorithms for Clustering (LEAC) is a library of genetic algorithms to solve the problem of partition clustering. It includes 22 classification genetic algorithms for solving ...

Algorithms are ubiquitous in medicine. They can take the form of a flowchart, a simple equation, or a complicated AI model, and are used to help clinicians diagnose diseases, predict the chances of ...

Clinical algorithms are tools that aid decision-making in a variety of medical conditions and procedures. Examples include diagnostic calculators that assess the current presence of a disease or ...

This is Part 1 of Embedded Bias, a series revealing how race-based clinical algorithms pervade medicine and why it's so difficult to change them. Pediatrician Alexandra Epee-Bounya had had enough. In ...

Health insurance companies cannot use algorithms or artificial intelligence to determine care or deny coverage to members on Medicare Advantage plans, the Centers for Medicare & Medicaid Services (CMS ...

The ability to quickly turn complex thoughts into clear visuals is invaluable in today’s fast-paced world. ChatGPT as a fantastically versatile tools that can help anyone from students to ...

Introduction: The retrospective analysis of continuous glucose monitoring (CGM) timeseries can be hampered by colored and non-stationary measurement noise. Here, we introduce a Bayesian denoising (BD) ...