A collaborative framework for contributing DICOM RT PHI (Protected Health Information) to augment data mining in clinical decision support

Deshpande, Ruchi; Thuptimdang, Wanwara; DeMarco, John J.; Liu, Brent J.

doi:10.1117/12.2044010

Cited by 2 publications

(3 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An interesting collection of topics presented included a remote volume rendering pipeline, 591 integration of medical images into a mobile device for bedside viewing, 592 and medical imaging document sharing using the IHE XDS profile. 593 Research data collections 594 and collaborative frameworks for data mining 595 were presented. Incorporating intelligence into structured radiology reports 596 was a paper of interest.…”

Section: S Pacs Conferencesmentioning

confidence: 99%

SPIE Medical Imaging 50th anniversary: history of the Picture Archiving and Communication Systems Conference

Andriole

2022

J. Med. Imag.

View full text Add to dashboard Cite

show abstract

Section: S Pacs Conferencesmentioning

confidence: 99%

SPIE Medical Imaging 50th anniversary: history of the Picture Archiving and Communication Systems Conference

Andriole

2022

J. Med. Imag.

View full text Add to dashboard Cite

show abstract

“…Tucker decomposition theorem: a tensor A ∈ R I1×···×I N can be expressed as where B is the core tensor; U (1) , U (2) , · · · , U (N ) are a series of orthogonal matrixes. Due to the orthogonality of the projection matrix U , core tensor B can be obtained by the above equation…”

Section: B Tensor and Tensor Decompositionmentioning

confidence: 99%

“…W ITH the development of information technology, the most advanced technologies are implemented in the field of health care [1] [2]. With the popularization of medical knowledge and the explosion of e-commerce, a growing number of people try to purchase medicine via online pharmacies, such as Drugstore [3].…”

Section: Introductionmentioning

confidence: 99%

COMER: Cloud-based medicine recommendation

Zhang

Wang

et al. 2014

10th International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness

View full text Add to dashboard Cite

With the development of e-commerce, a growing number of people prefer to purchase medicine online for the sake of convenience. However, it is a serious issue to purchase medicine blindly without necessary medication guidance. In this paper, we propose a novel cloud-based medicine recommendation, which can recommend users with top-N related medicines according to symptoms. Firstly, we cluster the drugs into several groups according to the functional description information, and design a basic personalized medicine recommendation based on user collaborative filtering. Then, considering the shortcomings of collaborative filtering algorithm, such as computing expensive, cold start, and data sparsity, we propose a cloud-based approach for enriching end-user Quality of Experience (QoE) of medicine recommendation, by modeling and representing the relationship of the user, symptom and medicine via tensor decomposition. Finally, the proposed approach is evaluated with experimental study based on a real dataset crawled from Internet.

show abstract

A collaborative framework for contributing DICOM RT PHI (Protected Health Information) to augment data mining in clinical decision support

Cited by 2 publications

References 2 publications

SPIE Medical Imaging 50th anniversary: history of the Picture Archiving and Communication Systems Conference

SPIE Medical Imaging 50th anniversary: history of the Picture Archiving and Communication Systems Conference

COMER: Cloud-based medicine recommendation

Contact Info

Product

Resources

About