Related papers: Surgical Data Science: A Consensus Perspective
The objective of the SPHERE Data Center is to optimize the scientific return of SPHERE at the VLT, by providing optimized reduction procedures, services to users and publicly available reduced data. This paper describes our motivation, the…
Data science has employed great research efforts in developing advanced analytics, improving data models and cultivating new algorithms. However, not many authors have come across the organizational and socio-technical challenges that arise…
Today, the prominence of data science within organizations has given rise to teams of data science workers collaborating on extracting insights from data, as opposed to individual data scientists working alone. However, we still lack a deep…
The proliferation of vast quantities of available datasets that are large and complex in nature has challenged universities to keep up with the demand for graduates trained in both the statistical and the computational set of skills…
A cross-disciplinary examination of the user behaviours involved in seeking and evaluating data is surprisingly absent from the research data discussion. This review explores the data retrieval literature to identify commonalities in how…
Many ground-breaking advancements in machine learning can be attributed to the availability of a large volume of rich data. Unfortunately, many large-scale datasets are highly sensitive, such as healthcare data, and are not widely available…
Across almost all scientific disciplines, the instruments that record our experimental data and the methods required for storage and data analysis are rapidly increasing in complexity. This gives rise to the need for scientific communities…
Most existing robotic surgery systems adopt a human-in-the-loop paradigm, often with the surgeon directly teleoperating the robotic system. Adding intelligence to these robots would enable higher-level control, such as supervised autonomy…
Due to the popularity of smart mobile phones and context-aware technology, various contextual data relevant to users' diverse activities with mobile phones is available around us. This enables the study on mobile phone data and…
In the field of machine learning, data understanding is the practice of getting initial insights in unknown datasets. Such knowledge-intensive tasks require a lot of documentation, which is necessary for data scientists to grasp the meaning…
Data sharing in the medical image analysis field has potential yet remains underappreciated. The aim is often to share datasets efficiently with other sites to train models effectively. One possible solution is to avoid transferring the…
We describe an introductory data science course, entitled Introduction to Data Science, offered at the University of Illinois at Urbana-Champaign. The course introduced general programming concepts by using the Python programming language…
Image-based tracking of medical instruments is an integral part of surgical data science applications. Previous research has addressed the tasks of detecting, segmenting and tracking medical instruments based on laparoscopic video data.…
Information and data exchange is an important aspect of scientific progress. In computational materials science, a prerequisite for smooth data exchange is standardization, which means using agreed conventions for, e.g., units, zero base…
Data forms a key component of any enterprise. The need for high quality and easy access to data is further amplified by organizations wishing to leverage machine learning or artificial intelligence for their operations. To this end, many…
Data Science---Today, everybody and everything produces data. People produce large amounts of data in social networks and in commercial transactions. Medical, corporate, and government databases continue to grow. Sensors continue to get…
Purpose: Data discovery practices currently tend to be studied from the perspective of researchers or the perspective of support specialists. This separation is problematic, as it becomes easy for support specialists to build…
High-quality data has become increasingly important to software engineers in designing and implementing today's software, for example, as an input to machine-learning algorithms and visualisation- and analytics-based features. Open data -…
This paper tries to throw light in the usage of data structures in the field of information retrieval. Information retrieval is an area of study which is gaining momentum as the need and urge for sharing and exploring information is growing…
Many have argued that statistics students need additional facility to express statistical computations. By introducing students to commonplace tools for data management, visualization, and reproducible analysis in data science and applying…