This paper is in the following e-collection/theme issue:

Clinical Mental Health Informatics (40) Machine Learning (1501) Artificial Intelligence (1421) Clinical Informatics (1050)

Published on in Vol 9, No 8 (2022): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38428, first published .
Predicting Patient Wait Times by Using Highly Deidentified Data in Mental Health Care: Enhanced Machine Learning Approach

Predicting Patient Wait Times by Using Highly Deidentified Data in Mental Health Care: Enhanced Machine Learning Approach

Predicting Patient Wait Times by Using Highly Deidentified Data in Mental Health Care: Enhanced Machine Learning Approach

Authors of this article:

Amir Rastpour1 Author Orcid Image ;   Carolyn McGregor1, 2 Author Orcid Image
Article Authors Cited by (5) Tweetations (3) Metrics

Journals

  1. Knights J, Bangieva V, Passoni M, Donegan M, Shen J, Klein A, Baker J, DuBois H. A framework for precision “dosing” of mental healthcare services: algorithm development and clinical pilot. International Journal of Mental Health Systems 2023;17(1) View
  2. Al‐Mousa A, Al‐Zubaidi H, Al‐Dweik M. A machine learning‐based approach for wait‐time estimation in healthcare facilities with multi‐stage queues. IET Smart Cities 2024 View
  3. Joseph J, Senith S, Kirubaraj A, Ramson S. Prediction of Consultation Wait Time in Outpatient Clinic: An Approach using Neural Network with Optimized Feature Selection. Procedia Computer Science 2024;233:129 View
  4. Baglini K, Bruns D, Hill J. Telemedicine as a Referral Bridge: A Nurse Practitioner–Led Intervention to Increase Initial Psychiatric Appointment Attendance. The Journal for Nurse Practitioners 2024;20(7):105068 View
  5. Aquino Y, Rogers W, Jacobson S, Richards B, Houssami N, Woode M, Frazer H, Carter S. Defining change: Exploring expert views about the regulatory challenges in adaptive artificial intelligence for healthcare. Health Policy and Technology 2024;13(3):100892 View