Abstract: Systems and methods are presented for scheduling appointments efficiently by generating predictive models using historical appointment data and using these models to predict in advance whether an appointment will be a no-show or a cancellation. The predictive models may be based on logistic regression methods, support vector machines, or neural networks. If the model predicts that an appointment in a particular time-slot will probably be a no-show/cancellation, a scheduling system may decide to double-book that time-slot in order to reduce scheduling inefficiency.

Abstract: A harness includes a single and unitary body with a plurality of longitudinal members and a plurality of latitudinal members monolithically formed therewith. The apparatus further includes a plurality of fasteners with opposed ends directly and oppositely mated to the longitudinal members and extending towards a center of the body for being engaged about the patient. Each of such fasteners has male and female members detachably and directly mated along a width of the body and between the longitudinal sides respectively. The apparatus further includes a first plurality of handles monolithically connected to the longitudinal members and extending laterally away therefrom along opposed sides of the body, and a second plurality of handles are monolithically connected to opposed corners of the body and diagonally protruding outwardly therefrom.