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Appointments and Schedules

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A machine learning framework for auto classification of imaging system exams in hospital setting for utilization optimization.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In clinical environment, Interventional X-Ray (IXR) system is used on various anatomies and for various types of the procedures. It is important to classify correctly each exam of IXR system into respective procedures and/or assign to correct anatomy...

Ubiquitous Multicriteria Clinic Recommendation System.

Journal of medical systems
Advancements in information, communication, and sensor technologies have led to new opportunities in medical care and education. Patients in general prefer visiting the nearest clinic, attempt to avoid waiting for treatment, and have unequal preferen...

Impact of predicting health-guidance candidates using massive health check-up data: A data-driven analysis.

International journal of medical informatics
INTRODUCTION: Starting in 2008, specific health checkups and health guidance to prevent non-communicable diseases have been provided in Japan, which has the highest proportion of elderly citizens in the world. The attendance rate for health guidance ...

Approximate dynamic programming approaches for appointment scheduling with patient preferences.

Artificial intelligence in medicine
During the appointment booking process in out-patient departments, the level of patient satisfaction can be affected by whether or not their preferences can be met, including the choice of physicians and preferred time slot. In addition, because the ...

Artificial Intelligence in Radiology: Current Technology and Future Directions.

Seminars in musculoskeletal radiology
Artificial intelligence (AI) has been heralded as the next big wave in the computing revolution and touted as a transformative technology for many industries including health care. In radiology, considerable excitement and anxiety are associated with...

Machine Learning Can Improve Estimation of Surgical Case Duration: A Pilot Study.

Journal of medical systems
Operating room (OR) utilization is a significant determinant of hospital profitability. One aspect of this is surgical scheduling, which depends on accurate predictions of case duration. This has been done historically by either the surgeon based on ...

Predicting Outpatient Appointment Demand Using Machine Learning and Traditional Methods.

Journal of medical systems
Traditional methods have long been used for clinical demand forecasting. Machine learning methods represent the next evolution in forecasting, but model choice and optimization remain challenging for achieving optimal results. To determine the best m...

Prediction of hospital no-show appointments through artificial intelligence algorithms.

Annals of Saudi medicine
BACKGROUND: No-shows, a major issue for healthcare centers, can be quite costly and disruptive. Capacity is wasted and expensive resources are underutilized. Numerous studies have shown that reducing uncancelled missed appointments can have a tremend...

Artificial Intelligence: A New Tool in Operating Room Management. Role of Machine Learning Models in Operating Room Optimization.

Journal of medical systems
We conducted a systematic review of literature to better understand the role of new technologies in the perioperative period; in particular we focus on the administrative and managerial Operating Room (OR) perspective. Studies conducted on adult (≥ 1...