11,759 research outputs found
Towards Personalized Prostate Cancer Therapy Using Delta-Reachability Analysis
Recent clinical studies suggest that the efficacy of hormone therapy for
prostate cancer depends on the characteristics of individual patients. In this
paper, we develop a computational framework for identifying patient-specific
androgen ablation therapy schedules for postponing the potential cancer
relapse. We model the population dynamics of heterogeneous prostate cancer
cells in response to androgen suppression as a nonlinear hybrid automaton. We
estimate personalized kinetic parameters to characterize patients and employ
-reachability analysis to predict patient-specific therapeutic
strategies. The results show that our methods are promising and may lead to a
prognostic tool for personalized cancer therapy.Comment: HSCC 201
Comparing Optimization Methods for Radiation Therapy Patient Scheduling using Different Objectives
Radiation therapy (RT) is one of the most common technologies used to treat
cancer. To better use resources in RT, optimization models can be used to
automatically create patient schedules, a task that today is done manually in
almost all clinics. This paper presents a comprehensive study of different
optimization methods for modeling and solving the RT patient scheduling
problem. The results can be used as decision support when implementing an
automatic scheduling algorithm in practice. We introduce an Integer Linear
Programming (IP) model, a column generation IP model (CG-IP), and a Constraint
Programming model. Patients are scheduled on multiple machine types considering
their priority for treatment, session duration and allowed machines, while
taking expected future patient arrivals into account. Different cancer centers
may have different scheduling objectives, and therefore each model is solved
using multiple different objective functions, including minimizing waiting
times, and maximizing the fulfillment of patients' preferences for treatment
times. The test data is generated from historical data from Iridium Netwerk, a
large cancer center in Belgium with 10 linear accelerators. The results
demonstrate that the CG-IP model can solve all the different problem instances
to a mean optimality gap of less than 1% within one hour. The proposed
methodology provides a tool for automated scheduling of RT treatments and can
be generally applied to RT centers.Comment: 20 pages, 4 figures, Submitted to Operations Research Foru
Automated Diagnosis of Clinic Workflows
Outpatient clinics often run behind schedule due to patients who arrive late
or appointments that run longer than expected. We sought to develop a
generalizable method that would allow healthcare providers to diagnose problems
in workflow that disrupt the schedule on any given provider clinic day. We use
a constraint optimization problem to identify the least number of appointment
modifications that make the rest of the schedule run on-time. We apply this
method to an outpatient clinic at Vanderbilt. For patient seen in this clinic
between March 27, 2017 and April 21, 2017, long cycle times tended to affect
the overall schedule more than late patients. Results from this workflow
diagnosis method could be used to inform interventions to help clinics run
smoothly, thus decreasing patient wait times and increasing provider
utilization
Head and neck cancer: metronomic chemotherapy
In the era of personalized medicine, head and neck squamous cell carcinoma (HNSCC) represents a critical oncologic topic. Conventional chemotherapy regimens consist of drugs administration in cycles near or at the maximum tolerated dose (MDT), followed by a long drug-free period to permit the patient to recover from acute toxicities. Despite this strategy is successful in controlling the cancer process at the beginning, a significant number of HNSCC patients tend to recurred or progress, especially those patients with locally advanced or metastatic disease. The repertoire of drugs directed against tumor cells has greatly increased and metronomic chemotherapy (MC) could be an effective treatment option.It is the purpose of this article to review the concept of MC and describe its potential use in HNSCC. We provide an update of ongoing progress and current challenges related to this issue
Targeted radiotherapy of neuroblastoma: future directions
No abstract available
An Automatic and Intelligent System for Integrated Healthcare Processes Management
In this work, an automatic and intelligent system for integrated healthcare processes
management is developed on a constraint based system. This project has been carried out in
collaboration with a real assisted repro-duction clinic. Our goal is to improve the efficiency of the
clinic by facilitating the management of the integrated healthcare system. This is very important
in an environment in which the healthcare processes present complex temporal and resource
constraints.Ministerio de EconomÃa y Competitividad TIN2016-76956-C3-2-RMinisterio de EconomÃa y Competitividad TIN2015-71938-RED
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