The Applications of Genetic Algorithms in Medicine

• Published in: Oman medical journal Vol. 30; no. 6; pp. 406 - 416
• Main Authors: Hoseini , Sayed Shahabuddin, Naderan , Mohammad, Shoar , Saeed, Ghaheri , Ali
• Format: Journal Article
• Language: English
• Published: Muscat - Oman Oman Medical Specialty Board 01.11.2015; OMJ
• Subjects: Algorithms; Cancer; Data processing; EVALUATION AND OPTIMIZATION; Genetic Algorithm; GENETIC ALGORITHMS; GENETICS; Heuristic algorithms; Heuristic methods; MEDICAL APPLICATIONS; MEDICAL SCIENCES; Medicine; Optimization; Review; Tomography; Tomography, Emission; التطبيقات الطبية; التقييم الأمثل; الخوارزميات الوراثية; العلوم الطبية; علم الوراثة; Medicine; Algorithms; Heuristic methods; Optimization; Genetic Algorithm
• ISSN: 1999-768X; 2070-5204
• DOI: 10.5001/omj.2015.82

A great wealth of information is hidden amid medical research data that in some cases cannot be easily analyzed, if at all, using classical statistical methods. Inspired by nature, metaheuristic algorithms have been developed to offer optimal or near-optimal solutions to complex data analysis and decision-making tasks in a reasonable time. Due to their powerful features, metaheuristic algorithms have frequently been used in other fields of sciences. In medicine, however, the use of these algorithms are not known by physicians who may well benefit by applying them to solve complex medical problems. Therefore, in this paper, we introduce the genetic algorithm and its applications in medicine. The use of the genetic algorithm has promising implications in various medical specialties including radiology, radiotherapy, oncology, pediatrics, cardiology, endocrinology, surgery, obstetrics and gynecology, pulmonology, infectious diseases, orthopedics, rehabilitation medicine, neurology, pharmacotherapy, and health care management. This review introduces the applications of the genetic algorithm in disease screening, diagnosis, treatment planning, pharmacovigilance, prognosis, and health care management, and enables physicians to envision possible applications of this metaheuristic method in their medical career.