While it is quite typical to deal with attributes of different data types in the visualization of heterogeneous and multivariate datasets, most existing techniques still focus on the most usual data types such as numerical attributes or strings. In this paper we present a new approach to the interactive visual exploration and analysis of data that contains attributes which are of set type. A set-typed attribute of a data item--like one cell in a table--has a list of n > or = 0 elements as its value. We present the set'o'gram as a new visualization approach to represent data of set type and to enable interactive visual exploration and analysis. We also demonstrate how this approach is capable to help in dealing with datasets that have a larger number of dimensions (more than a dozen or more), especially also in the context of categorical data. To illustrate the effectiveness of our approach, we present the interactive visual analysis of a CRM dataset with data from a questionnaire on the education and shopping habits of about 90000 people.
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http://dx.doi.org/10.1109/TVCG.2008.144 | DOI Listing |
BMC Med Educ
January 2025
Department of Physiology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
Background: The doctor-patient relationship is essential for effective patient care, yet medical education often neglects to nurture the quality such as empathy during the initial years of training. Doctor-patient relationship is one of the modules taught in first year as part of mandatory AETCOM (Attitude, Ethics, and Communication) course in the undergraduate Indian medical curriculum. Hermeneutics, a method of interpretation, can play a vital role in introducing observational and reflective thinking skills.
View Article and Find Full Text PDFSci Rep
January 2025
Guangzhou Municipal and Guangdong Provincial Key Laboratory of Protein Modification and Disease, School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou, 511436, China.
Hepatocellular carcinoma (HCC) is the most prevalent form of primary liver cancer, notoriously refractory to conventional chemotherapy. Historically, sulfane sulfur-based compounds have been explored for the treatment of HCC, but their efficacy has been underwhelming. We recently reported a novel sulfane sulfur donor, PSCP, which exhibited improved chemical stability and structural malleability.
View Article and Find Full Text PDFEur J Nucl Med Mol Imaging
January 2025
Institute of Radiation Medicine, Fudan University, Xietu Road 2094, Shanghai, 200032, China.
Objectives: Mesothelin (MSLN) is an antigen that is overexpressed in various cancers, and its interaction with tumor-associated cancer antigen 125 plays a multifaceted role in tumor metastasis. The serum MSLN expression level can be detected using enzyme-linked immunosorbent assay; however, non-invasive visualization of its expression at the tumor site is currently lacking. Therefore, the aim of this study was to develop a molecular probe for imaging MSLN expression through positron emission tomography (PET).
View Article and Find Full Text PDFActa Paediatr
January 2025
Paediatric Neurology and Neurorehabilitation Unit, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
Aim: Young people with childhood-onset motor disabilities face unique challenges in understanding and managing their condition. This study explored how they learnt about their condition.
Method: A descriptive qualitative study was conducted in 2023-2024 at a Swiss paediatric neurorehabilitation unit.
J Chem Inf Model
January 2025
School of Information Science & Engineering, Lanzhou University, Lanzhou 730000, China.
Efficient and accurate drug-target affinity (DTA) prediction can significantly accelerate the drug development process. Recently, deep learning models have been widely applied to DTA prediction and have achieved notable success. However, existing methods often encounter several common issues: first, the data representations lack sufficient information; second, the extracted features are not comprehensive; and third, most methods lack interpretability when modeling drug-target binding.
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