Natural language processing is becoming ever more important in research. The explosion in interest in LLMs is sparking many opportunities to analyse text data in healthcare, social sciences, and other areas.
We’re proud to announce that the Clinical Trial Risk Tool has been selected as a winner of the Plotly Dash Example Apps Challenge (2023), out of 25 amazing apps submitted by the community.
Funded by the Bill and Melinda Gates Foundation, this app uses natural language processing, Plotly Dash, and the spaCy and Scikit-Learn libraries to calculate the risk of a clinical trial failing to deliver informative results. It reads the trial protocol and identifies key features from the text which are fed into a risk model.
Join Plotly’s webinar to see the tool in action! https://tinyurl.com/4zd3emkr
You can try the new version of the app at: https://clinical.fastdatascience.com
You can try version 1.0 of the app (using Plotly Dash) at: https://clinical.fastdatascience.com/login?guest=true/.
Wood TA and McNair D. Clinical Trial Risk Tool: software application using natural language processing to identify the risk of trial uninformativeness. Gates Open Res 2023, 7:56 (https://doi.org/10.12688/gatesopenres.14416.1).
This post originally appeared on Fast Data Science’s blog on LinkedIn. Clinical trials are essential for medical advancement but are not without risk. Delays, budget overruns, and compliance issues can derail the most carefully planned studies. Proactive risk management is the key to ensuring patient safety, maintaining regulatory compliance, and achieving successful trial outcomes. In this article we’ll explore the key risks in clinical trials, how AI-powered tools like the Clinical Trial Risk Tool can help mitigate these risks, and practical strategies for ongoing risk monitoring.
This post originally appeared on Fast Data Science’s blog on LinkedIn. Discover how the Clinical Trial Risk Tool helps optimise clinical trial workflows with accurate risk and cost analysis. Save time and reduce costs. Why Workflow Efficiency Matters in Clinical Trials Running a clinical trial is a complex and expensive process. Delays, unexpected costs, and inefficiencies can waste time and money, affecting trial outcomes and patient care. As trials become more complicated, workflow management is more important than ever.
This post originally appeared on Fast Data Science’s blog on LinkedIn. In today’s ever-evolving healthcare landscape, technology is crucial to improving patient care, streamlining processes, and enhancing outcomes. Natural Language Processing (NLP) is one such technology that is revolutionising the way healthcare organisations operate. For instance, NLP has been used to analyse patient feedback and identify trends in satisfaction levels, leading to targeted improvements in service quality. In this article, we will explore the role of NLP in healthcare, its benefits, and potential applications.
