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Hamideh Anjomshoa

Bio: Hamideh Anjomshoa is an academic researcher from IBM. The author has contributed to research in topics: Haulage & Schedule. The author has an hindex of 4, co-authored 10 publications receiving 37 citations. Previous affiliations of Hamideh Anjomshoa include University of South Africa & University of South Australia.

Papers
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Journal ArticleDOI
TL;DR: In this article, the authors investigate the association between 21 preoperative factors and speech recognition approximately one year after implantation and explore the consistency of their effects across the three constituent datasets.
Abstract: While the majority of cochlear implant recipients benefit from the device, it remains difficult to estimate the degree of benefit for a specific patient prior to implantation. Using data from 2,735 cochlear-implant recipients from across three clinics, the largest retrospective study of cochlear-implant outcomes to date, we investigate the association between 21 preoperative factors and speech recognition approximately one year after implantation and explore the consistency of their effects across the three constituent datasets. We provide evidence of 17 statistically significant associations, in either univariate or multivariate analysis, including confirmation of associations for several predictive factors, which have only been examined in prior smaller studies. Despite the large sample size, a multivariate analysis shows that the variance explained by our models remains modest across the datasets (R2=0.12-0.21). Finally, we report a novel statistical interaction indicating that the duration of deafness in the implanted ear has a stronger impact on hearing outcome when considered relative to a candidate's age. Our multicenter study highlights several real-world complexities that impact the clinical translation of predictive factors for cochlear implantation outcome. We suggest several directions to overcome these challenges and further improve our ability to model patient outcomes with increased accuracy.

29 citations

Journal ArticleDOI
TL;DR: A multiple objective mixed integer programming model of this problem can provide insightful information to decision makers in the hospital whether they can meet their KPIs with their current resources and also the effect of increasing resources on various KPIs.

17 citations

Journal ArticleDOI
Ashwani Kumar1, Hamideh Anjomshoa1
TL;DR: A two-stage classification model to classify patients into lower variability resource user groups by using electronic patient records is developed and it is found that the CART analysis is also useful for determining the patient attributes that can explain the variability in resource requirements.
Abstract: Soaring healthcare costs and the growing demand for services require us to use healthcare resources more efficiently. Randomness in resource requirements makes the care delivery process less efficient. Our aim is to reduce the uncertainty in patients’ resource requirements, and we achieve that objective by classifying patients into similar resource user groups. In this article, we develop a two-stage classification model to classify patients into lower variability resource user groups by using electronic patient records. There are various statistical tools for classifying patients into lower variability resource user groups. However, classification and regression tree (CART) analysis is a more suitable method for analyzing healthcare data because it has some distinct features. For example, it can handle the interaction between predictor variables naturally, it is nonparametric in nature, and it is relatively insensitive to the curse of dimensionality. We found that the CART analysis is also useful for determining the patient attributes that can explain the variability in resource requirements. Furthermore, we observed that some of the covariates, such as the principal prescribed procedure code, the admission point, and the operating surgeon, were able to explain up to $53.43\%$ of the variability in patients’ lengths of stay (LoS). Reducing the uncertainty in patients’ LoS predictions helps us manage patient flow efficiently and subsequently obtain a better throughput.

12 citations

Journal ArticleDOI
TL;DR: This paper organizes the principles of resilience principles at the systems level into a conceptual framework for resilient design, which includes a set of nonfunctional requirements for resilience and an assessment methodology for evaluating architectural work from a resilience standpoint.
Abstract: Resilience is often a qualitative property that is considered fundamental for communities affected by disasters. The concept, along with its variations, has been explored in several domains, such as warfare, business continuity, ecology, computer security, and infrastructure management. The lessons learned constitute a valuable starting point for building resilient socio-technical systems. In previous work, we have described resilience principles at the systems level by reviewing related studies in several research areas. This paper organizes the principles into a conceptual framework for resilient design, which includes a set of nonfunctional requirements for resilience and an assessment methodology for evaluating architectural work from a resilience standpoint. After having presented this conceptual framework, we discuss its application in our collaboration with the Victorian Fire Services Commissioner. This collaboration has led to the specification of a high-level reference architecture for the information interoperability platform that will support emergency services in Victoria.

8 citations

Journal ArticleDOI
TL;DR: A mixed integer programming (MIP) model is formulated and solved to determine the optimal locations of passing bays to maximise haulage productivity for given numbers of vehicles and passed bays.
Abstract: In many underground mines, haulage vehicles carry ore from underground loading stations to the surface. Vehicles travel in narrow tunnels with occasional passing bays that allow descending empty vehicles to pull off the main path and wait for ascending laden vehicles to pass. The number of passing bays and their locations influence the delays to descending vehicles, and hence the haulage productivity of the mine. We formulate and solve a mixed integer programming (MIP) model to determine the optimal locations of passing bays to maximise haulage productivity for given numbers of vehicles and passing bays. The MIP also generates the corresponding vehicle schedule. Previous studies have only examined the placement of equally spaced bays. The results obtained from the MIP show that this is not always optimal. Furthermore, we observe that the best locations of passing bays are those that allow interleaving of vehicles without delays at bays.

4 citations


Cited by
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Journal ArticleDOI
TL;DR: The findings of a comprehensive literature survey aimed at shedding light on emerging concepts and approaches to handle disruptions in business ecosystems are introduced.

72 citations

Journal ArticleDOI
TL;DR: This review summarized and synthesized the literature that examined resilience in the context of emergency management (EM), and identified five prevalent technical tools used to enhance resilience in EM: mapmaking, event history logging, mobile communication applications, integrated information management system, and decision support tools.

41 citations

Journal ArticleDOI
TL;DR: A stochastic mixed integer programming model is developed to optimise the tactical master surgery schedule (MSS) in order to achieve a better patient flow under downstream capacity constraints and develops a robust MSS to maximise the utilisation level while keeping the number of cancellations within acceptable limits.

30 citations

Journal ArticleDOI
Devendra P. Garg1
01 Aug 1975

22 citations

Journal ArticleDOI
TL;DR: A green project scheduling model of port construction is presented to optimize comprehensive economic and environmental efficiency and shows that a representative port in China can save 6,527 tons of standard coal, reduce 40,875 tons of CO2, and save 49 million yuan per year in the five-year implementation period.
Abstract: Ports are an important driving force for world economic growth, but they consume considerable energy. The marine sector has proposed the development of green ports to achieve low-carbon sus...

19 citations