الفهرس 
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Abstract
Since the wide use of computer aided systems in healthcare sector, vast
amount of medical databases established. Those historical data used to set up
descriptive and predictive applications using data mining and intelligent
techniques. As a result, those techniques successfully built models which help
administration and decision makers to enhance hospitals performance
management in (treatment cost control, staff allocation and evaluation,
demographic and market trends, quality assurance, process efficiency and
improving healthcare quality). As well as, clinical decisions (disease
diagnosis, medication plan, diseases early detection, mortality early detection,
detecting high risk patients, etc.)
According to the World Health Organization (WHO), one of the performance
measurements and monitoring indicators is the hospitals’ length of staying and
it also used to evaluate both financial and medical performance
Prolonged Length of Stay (LOS) in Intensive Care Unit (ICU) leads to
consuming hospitals resources as manpower and equipment. Moreover
increase patients’ recovery duration and raising the probability of death during
accommodation or after discharging. So, predicting LOS aims to best
resources utilization and medical team allocation. Additionally, helping the
healthcare specialists for more effective medical decision making. Increasing
cost for ICU bed equipment and operating expenses lead to shortage in ICU
beds. Therefore, providing health care providers with information about
expected discharge dates helps more patients waiting for an empty bed as well
as accounting department can recognize the amount of the initial insurance
paid in cash for patients who do not have medical insurance.
Furthermore, healthcare insurance companies can evaluate the expected cost
for their clients and the quality of healthcare they receive.
Researches provided in this area are interested in predicting the LOS for a
particular diagnosis or complains for the patients who suffer from cancer,
diabetes or even after a specific surgery; therefore, researches could afford
having accepted prediction accuracy, especially when specific features in the
evaluation and modeling were in use.