AIMC Topic: Waiting Lists
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Prediction of hospitalization and waiting time within 24 hours of emergency department patients with unstructured text data.
Health care management science
Nov 3, 2023
Overcrowding of emergency departments is a global concern, leading to numerous negative consequences. This study aimed to develop a useful and inexpensive tool derived from electronic medical records that supports clinical decision-making and can be ...
Deep Learning-Based Survival Analysis for Receiving a Steatotic Donor Liver Versus Waiting for a Standard Liver.
Transplantation proceedings
Oct 22, 2023
BACKGROUND: An emerging strategy to expand the donor pool is the use of a steatotic donor liver (SDLs; ≥ 30% macrosteatosis on biopsy). With the obesity epidemic and prevalence of nonalcoholic fatty liver disease, SDLs have been reported in 59% of al...
Ranking patients on the kidney transplant waiting list based on fuzzy inference system.
BMC nephrology
Jan 15, 2022
BACKGROUND: Kidney transplantation is the best treatment for people with End-Stage Renal Disease (ESRD). Kidney allocation is the most important challenge in kidney transplantation process. In this study, a Fuzzy Inference System (FIS) was developed ...
Identifying scenarios of benefit or harm from kidney transplantation during the COVID-19 pandemic: A stochastic simulation and machine learning study.
American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
Jul 15, 2020
Clinical decision-making in kidney transplant (KT) during the coronavirus disease 2019 (COVID-19) pandemic is understandably a conundrum: both candidates and recipients may face increased acquisition risks and case fatality rates (CFRs). Given our po...
Predicting Outpatient Appointment Demand Using Machine Learning and Traditional Methods.
Journal of medical systems
Jul 19, 2019
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...
Machine Learning for Predicting Patient Wait Times and Appointment Delays.
Journal of the American College of Radiology : JACR
Oct 24, 2017
Being able to accurately predict waiting times and scheduled appointment delays can increase patient satisfaction and enable staff members to more accurately assess and respond to patient flow. In this work, the authors studied the applicability of m...
Ubiquitous Multicriteria Clinic Recommendation System.
Journal of medical systems
Mar 17, 2016
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...
Machine Learning for Predicting Waitlist Mortality in Pediatric Heart Transplantation.
Pediatric transplantation
Jun 1, 2025
BACKGROUND: Waitlist mortality remains a critical issue for pediatric heart transplant (HTx) candidates, particularly for candidates with congenital heart disease. Listing center organ offer acceptance practices have been identified as a factor influ...
Analysis of the most influential factors affecting outcomes of lung transplant recipients: a multivariate prediction model based on UNOS Data.
BMJ open
May 16, 2025
OBJECTIVES: In lung transplantation (LTx), a priority is assigned to each candidate on the waiting list. Our primary objective was to identify the key factors that influence the allocation of priorities in LTx using machine learning (ML) techniques t...
Applying Artificial Intelligence to Quantify Body Composition on Abdominal CTs and Better Predict Kidney Transplantation Wait-List Mortality.
Journal of the American College of Radiology : JACR
Mar 1, 2025
BACKGROUND: Prekidney transplant evaluation routinely includes abdominal CT for presurgical vascular assessment. A wealth of body composition data are available from these CT examinations, but they remain an underused source of data, often missing fr...
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