Related papers: Spreadsheets in Clinical Medicine
Clinical trials are an indispensable part of the drug development process, bridging the gap between basic research and clinical application. During the development of new drugs, clinical trials are used not only to evaluate the safety and…
Spreadsheet engineering adapts the lessons of software engineering to spreadsheets, providing eight principles as a framework for organizing spreadsheet programming recommendations. Spreadsheets raise issues inadequately addressed by…
Several problems in healthcare stem from the complex network of intermediaries and the lack of traceability of transactions. To mention a few: healthcare data is fragmented across several silos negatively affecting research and services,…
As computational analysis becomes increasingly more complex in health research, transparent sharing of analytical code is vital for reproducibility and trust. This practical guide, aligned to open science practices, outlines actionable…
Machine Learning (ML) research has increased substantially in recent years, due to the success of predictive modeling across diverse application domains. However, well-known barriers exist when attempting to deploy ML models in high-stakes,…
We consider a patient risk models which has access to patient features such as vital signs, lab values, and prior history but does not have access to a patient's diagnosis. For example, this occurs in a model deployed at intake time for…
Clinical prediction models are statistical or machine learning models used to quantify the risk of a certain health outcome using patient data. These can then inform potential interventions on patients, causing an effect called performative…
This paper presents the results of an empirical evaluation of the quality of a structured methodology for the development of spreadsheet models, proposed in numerous previous papers by Rajalingham K, Knight B and Chadwick D et al. This…
In traditional usability studies, researchers talk to users of tools to understand their needs and challenges. Insights gained via such interviews offer context, detail, and background. Due to costs in time and money, we are beginning to…
The use of spreadsheets in industry is widespread. Companies base decisions on information coming from spreadsheets. Unfortunately, spreadsheets are error-prone and this increases the risk that companies base their decisions on inaccurate…
A spreadsheet is remarkably flexible in representing various forms of structured data, but the individual cells have no knowledge of the larger structures of which they may form a part. This can hamper comprehension and increase formula…
The construction of mathematical models that allow comprehensive approach of decision-making in situations of absence of robust evidence is important. While it is interesting to use models that are easy to understand, using values of direct…
Just like other software, spreadsheets can contain significant faults. Static analysis is an accepted and well-established technique in software engineering known for its capability to discover faults. In recent years, a growing number of…
Artificial intelligence (AI) is expected to revolutionize the practice of medicine. Recent advancements in the field of deep learning have demonstrated success in a variety of clinical tasks: detecting diabetic retinopathy from images,…
The spreadsheet has been used by the business community for many years and yet still raises a number of significant concerns. As educators our concern is to try to develop the students skills in both the development of spreadsheets and in…
In a data-scarce field such as healthcare, where models often deliver predictions on patients with rare conditions, the ability to measure the uncertainty of a model's prediction could potentially lead to improved effectiveness of decision…
Livestock industries are vulnerable to disease threats, which can cost billions of dollars and have substantial negative social ramifications. Losses are mitigated through increased use of disease-related biosecurity practices, making…
The usual aim of spreadsheet audit is to verify correctness. There are two problems with this: first, it is often difficult to tell whether the spreadsheets in question are correct, and second, even if they are, they may still give the…
We have conducted an empirical investigation into the long term survival rates of some small but representative samples of the 30,000 largest UK limited companies. These companies were either a control or known to have used, or been…
Academic medical centers are generating an increasing amount of biomedical data and there is an increasing demand for biomedical data for research purposes by research projects, research consortia, companies, and other third parties. At the…