AIMC Topic: Appointments and Schedules
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A Novel Natural Language Processing Model for Triaging Head and Neck Patient Appointments.
Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
Apr 25, 2025
OBJECTIVE: Inaccurate patient triage contributes to suboptimal clinical capacity management and delays in patient care, which in cancer patients may significantly increase morbidity and mortality. We developed a natural language processing (NLP) mode...
Innovative Technologies for Smarter and Efficient Operating Room Scheduling.
Journal of medical systems
Mar 21, 2025
An optimized scheduling system for surgical procedures is considered fundamental for maximizing hospital resource utilization and improving patient outcomes. The integration of Artificial Intelligence (AI) tools and New Technologies is paramount in t...
Predictive Optimization of Patient No-Show Management in Primary Healthcare Using Machine Learning.
Journal of medical systems
Jan 14, 2025
The "no-show" problem in healthcare refers to the prevalent phenomenon where patients schedule appointments with healthcare providers but fail to attend them without prior cancellation or rescheduling. In addressing this issue, our study delves into ...
Real-Time Analytics and AI for Managing No-Show Appointments in Primary Health Care in the United Arab Emirates: Before-and-After Study.
JMIR formative research
Jan 6, 2025
BACKGROUND: Primary health care (PHC) services face operational challenges due to high patient volumes, leading to complex management needs. Patients access services through booked appointments and walk-in visits, with walk-in visits often facing lon...
Utilization of Machine Learning Models to More Accurately Predict Case Duration in Primary Total Joint Arthroplasty.
The Journal of arthroplasty
Oct 28, 2024
BACKGROUND: Accurate operative scheduling is essential for the appropriation of operating room esources. We sought to implement a machine learning model to predict primary total hip arthroplasty (THA) and total knee arthroplasty (TKA) case time.
Enhancing Aortic Aneurysm Surveillance: Transformer Natural Language Processing for Flagging and Measuring in Radiology Reports.
Annals of vascular surgery
Oct 16, 2024
BACKGROUND: Incidental findings of aortic aneurysms (AAs) often go unreported, and established patients are frequently lost to follow-up. Natural language processing (NLP) offers a promising solution to address these issues. While rule-based NLP meth...
[Prioritized appointment allocation in new patients, what is really decisive? : Comparative analysis of manual appointment allocation with automated and AI-assisted approaches].
Zeitschrift fur Rheumatologie
Aug 16, 2024
BACKGROUND: The timely allocation of appointments for new patients is a daily challenge in rheumatological practice, which can be supported by digital solutions. The question is to find the simplest and most effective possible method for prioritizati...
Revolutionizing Schedules: The Power of AI in Physician Practices.
Frontiers of health services management
May 24, 2024
Since the early 2000s, artificial intelligence (AI) has raised concerns regarding its use in healthcare to manage vast amounts of patient data, ensure proper handling, and maintain robust security measures. Nevertheless, contemporary healthcare organ...
Machine Learning-Based Approach to Predict Last-Minute Cancellation of Pediatric Day Surgeries.
Computers, informatics, nursing : CIN
May 1, 2024
The last-minute cancellation of surgeries profoundly affects patients and their families. This research aimed to forecast these cancellations using EMR data and meteorological conditions at the time of the appointment, using a machine learning approa...
Appointment Scheduling Problem in Complexity Systems of the Healthcare Services: A Comprehensive Review.
Journal of healthcare engineering
Mar 3, 2022
This paper provides a comprehensive review of Appointment Scheduling (AS) in healthcare service while we propose appointment scheduling problems and various applications and solution approaches in healthcare systems. For this purpose, more than 150 s...
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