RCDVis: interactive rare category detection on graph data

Author(s):  
Aijuan Qian ◽  
Xiaoju Dong ◽  
Yanling Zhang ◽  
Chenlu Li
Keyword(s):  
2020 ◽  
Vol 16 (1) ◽  
Author(s):  
Mona Lundin

This study explores the use of a new protocol in hypertension care, in which continuous patient-generated data reported through digital technology are presented in graphical form and discussed in follow-up consultations with nurses. This protocol is part of an infrastructure design project in which patients and medical professionals are co-designers. The approach used for the study was interaction analysis, which rendered possible detailed in situ examination of local variations in how nurses relate to the protocol. The findings show three distinct engagements: (1) teasing out an average blood pressure, (2) working around the protocol and graph data and (3) delivering an analysis. It was discovered that the graphical representations structured the consultations to a great extent, and that nurses mostly referred to graphs that showed blood pressure values, which is a measurement central to the medical discourse of hypertension. However, it was also found that analysis of the data alone was not sufficient to engage patients: nurses' invisible and inclusion work through eliciting patients' narratives played an important role here. A conclusion of the study is that nurses and patients both need to be more thoroughly introduced to using protocols based on graphs for more productive consultations to be established. 


2012 ◽  
Vol 23 (5) ◽  
pp. 1195-1206
Author(s):  
Hao HUANG ◽  
Qin-Ming HE ◽  
Qi CHEN ◽  
Feng QIAN ◽  
Jiang-Feng HE ◽  
...  

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sawsan Ismail ◽  
Munawar Hraib ◽  
Rana Issa ◽  
Thanaa Alassi ◽  
Zuheir Alshehabi

Abstract Background Ovarian steroid cell tumors represent a rare category of sex cord-stromal tumors that constitute less than 0.1% of all ovarian tumors. These neoplasms are classified into three main subtypes according to the cell of origin: Leidyg cell tumors, stromal luteomas, and steroid cell tumors not otherwise specified (SCTs-NOS). The latter subtype is defined as a neoplasm of an uncertain lineage that mostly affects middle-aged women, whereas it’s rare in younger ages. Case presentation We report a case of a 21-year-old virgin female who presented to our hospital with complaints of mild abdominal pain, hirsutism, and oligomenorrhea for more than a year. Before her current admission, the patient had attended an external gynecologic clinic where she had been prescribed oral contraceptives to regulate her periods. Nevertheless, on presentation to our institution, physical examination revealed abdominal tenderness with a palpable pelvic mass and mild hirsutism in the thigh. Ultrasonography demonstrated a large left ovarian mass measuring 154 × 104 mm, and compressing the uterus. Therefore, a unilateral salpingo-oophorectomy was performed, and interestingly, pathologic examination of the large aforementioned mass alongside with immunohistochemical correlation revealed the diagnosis of a large ovarian steroid cell tumor-not otherwise specified with a unique combination of benign and malignant features. Conclusions Although ovarian steroid cell tumors represent a rare category, they must be considered in the differential diagnosis for mild virilization symptoms in young females due to the importance of early diagnosis and management. In this manuscript, we aimed to present the first case report from Syria that highlights the crucial role of detailed morphological examination for challenging cases despite the difficulties in differential diagnosis, and the absence of ancillary techniques. Furthermore, we managed to discuss a brief review of diagnostic methods, histological characteristics, and treatment recommendations.


Author(s):  
Marcus Paradies ◽  
Stefan Plantikow ◽  
Oskar van Rest

2019 ◽  
Vol 30 (4) ◽  
pp. 24-40
Author(s):  
Lei Li ◽  
Fang Zhang ◽  
Guanfeng Liu

Big graph data is different from traditional data and they usually contain complex relationships and multiple attributes. With the help of graph pattern matching, a pattern graph can be designed, satisfying special personal requirements and locate the subgraphs which match the required pattern. Then, how to locate a graph pattern with better attribute values in the big graph effectively and efficiently becomes a key problem to analyze and deal with big graph data, especially for a specific domain. This article introduces fuzziness into graph pattern matching. Then, a genetic algorithm, specifically an NSGA-II algorithm, and a particle swarm optimization algorithm are adopted for multi-fuzzy-objective optimization. Experimental results show that the proposed approaches outperform the existing approaches effectively.


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