We investigate the scheduling practices of a multidisciplinary, multistage, outpatient health
care program. Patients undergo a series of assessments before being eligible for elective …

Abstract Knowledge-based planning (KBP) is an automated approach to radiation therapy
treatment planning that involves predicting desirable treatment plans before they are then …

We study a double-sided queue with batch arrivals and abandonment. There are two types
of customers, patient ones who queue but may later abandon, and impatient ones who …

We investigate the trade‐off between acquisition and retention efforts when customers are
sensitive to the quality of service they receive, that is, whether they get timely access to a …

We investigate the scheduling practices of a medical school that must assign a cohort of
students to a series of clinical rotations, while respecting both operational and quality‐of‐service …

Purpose To develop a knowledge‐based automated planning pipeline that generates
treatment plans without feature engineering, using deep neural network architectures for …

Background Obesity is a global epidemic, and several surgical programs have been created
to combat this public health issue. Although demand for bariatric surgery has grown, so too …

We investigate the inventory management practices for reusable surgical instruments that
must be sterilized between uses. We study a hospital that outsources their sterilization …

We analyze a double-sided queue with priority that serves patient customers and customers
with zero patience (ie, impatient customers). In a two-sided market, high and low priority …

We determine how prediction methods combine with optimization methods in two-stage
knowledge-based planning (KBP) pipelines to produce radiation therapy treatment plans. We …