SLC

Research Unmuted

Science EN ↓ 7 episodes

Research Unmuted is a experimental scientific audio journal presenting contemporary research in diabetes, cardiometabolic diseases, prediabetes, wearable technology, digital health, medical informatics, data science, AI, machine learning, and related topics. Episodes discuss peer-reviewed studies, methodological insights, and clinical implications, translating complex research into an accessible format.

Author

SLC

Category

Science

Podcast website

research-unmuted.uk

Latest episode

Apr 17, 2026

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Episodes

Can ChatGPT Count Your Carbs? 17.04.2026

Abstract Introduction:Type 1 diabetes mellitus (T1D) requires precise carbohydrate estimation to manage blood glucose and prevent chronic and acute complications to hyperglycemia or hypoglycemia. This study evaluates the accuracy of ChatGPT in estimating carbohydrate content in images of meals, compared with the considered gold standard of manually counting carbohydrates. Method:Carbohydrate conte...

The A1c Mystery 19.02.2026

Abstract This study aims to characterize the temporal discordance between CGM-derived glucose exposure and HbA1c over time in individuals with type 1 diabetes, and to explore the development of a statistical model to adjust the relationship between these measures based on previously observed individual discrepancies. We paired CGM-data in a 60-day window prior to each HbA1c measurement and include...

What Research Should be Prioritized in Prediabetes 20.01.2026

Abstract Aims/hypothesis: Research agendas are typically set by researchers and funders, meaning that priorities of end users, such as patients and healthcare professionals (HCPs), could be missed or overlooked in research. To ensure future research in prediabetes is of relevance and benefit to people with prediabetes and HCPs, it is important to involve these stakeholders in setting the research...

Reproducibility in the Age of Data-Driven Research 20.01.2026

Abstract Sharing research code in an open access version-controlled repository offers significant benefits for both science as a whole and for individual researchers. In this article, we focus on this practice, which is fully aligned with the NIH’s Gold Standard Science (GSS) program as well as FAIR (findable, accessible, interoperable, reusable) and TRUST (transparency, responsibility, user focus...

Learning From Irregular Data 06.01.2026

Abstract Accurately predicting blood glucose (BG) levels of ICU patients is critical, as both hypoglycemia (BG < 70 mg/dL) and hyperglycemia (BG > 180 mg/dL) are associated with increased morbidity and mortality. This study presents a proof-of-concept machine learning framework, the Multi-source Irregular Time-Series Transformer (MITST), designed to predict BG levels in ICU patients. In cont...

What CGM Data Gaps Are Really Telling Us 02.01.2026

Abstract The aim was to investigate the association between continuous glucose monitoring (CGM) data coverage and glycemic metrics. This study included over 97,000 clinical study participants and real-world data from type 1 or type 2 diabetes treated with multiple daily insulin injections, closed-loop systems, or basal-only insulin regimens. Over 35 million days of CGM data were analyzed with mult...

Editorial 02.01.2026

Research Unmuted beta is a experimental audio overview platform designed for the researcher, students and people interested in science. We transform complex, peer-reviewed publications into high-fidelity audio summaries and podcasts, allowing you to listen. Citation Cichosz, S. (2026, januar 2). Research Unmuted – Episode 1: Editorial. Research Unmuted. https://doi.org/10.5281/zenodo.18171055 Tags...

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