25 papers · ranked by Valyu relevance
Hyerim Park, Khanh Huynh, Malin Eiband, Jeremy Dillmann + 2 more
Generative AI (GenAI) systems are inherently non-deterministic, producing varied outputs even for identical inputs. While this variability is central to their appeal, it challenges established HCI evaluation practices that typically assume consistent and predictable system behavior. Designing controlled lab studies…
Lili Wei, Ellen Kuenzig, James Im, Yan Zheng + 24 more
Routinely collected health data (RCD) including electronic health records, disease registries, health administrative data and wearables data are not specifically collected for research purposes. Analysis of these data poses unique methodological challenges that must be addressed when conducting research, particularly…
Katy Davis, Nicole Minckas, Virginia Bond, Cari Jo Clark + 14 more
Background Randomised controlled trials (RCTs) are widely used for establishing evidence of the effectiveness of interventions, yet public health interventions are often complex, posing specific challenges for RCTs. Although there is increasing recognition that qualitative methods can and should be integrated into…
Anna-Marie Wium, Brenda Louw
Background: Mixed-methods research (MMR) offers much to healthcare professions on clinical and research levels. Speech-language therapists and audiologists work in both educational and health settings where they deal with real-world problems. Through the nature of their work, they are confronted with multifaceted…
Berna Devezer, Danielle J. Navarro, Joachim Vandekerckhove, Erkan Ozge Buzbas
Current attempts at methodological reform in sciences come in response to an overall lack of rigor in methodological and scientific practices in experimental sciences. However, some of these reform attempts suffer from the same mistakes and over-generalizations they purport to address. Considering the costs of allowing…
Frantis̆ek Bartos̆, Samuel Pawel, Björn S. Siepe
Simulation studies are widely used to evaluate statistical methods. However, new methods are often introduced and evaluated using data-generating mechanisms (DGMs) devised by the same authors. This coupling creates misaligned incentives, e.g., the need to demonstrate the superiority of new methods, potentially…
Martin Amezcua, David Mobley
The SAMPL challenges focus on testing and driving progress of computational methods to help guide pharmaceutical drug discovery. However, assessment of methods for predicting binding affinities is often hampered by computational challenges such as conformational sampling, protonation state uncertainties, variation in…
Theo Lorenc, Lambert Felix, Mark Petticrew, G J Melendez-Torres + 4 more
'James Thomas' 'Sian Thomas' 'Alison O’Mara-Eves' 'Michelle Richardson'] Background Complex or heterogeneous data pose challenges for systematic review and meta-analysis. In recent years, a number of new methods have been developed to meet these challenges. This qualitative interview study aimed to understand…
Jéssica Lígia Picanço Machado, Ana Paula Schaan, Izabela Mamede, Gabriel da Rocha Fernandes
Diabetes mellitus is a prevalent chronic non-communicable disease, and recent studies have explored the link between gut microbiota and its development. Despite some evidence suggesting an association, the influence of gut microbiota on type 2 diabetes DM2 remains unclear. A systematic search of PubMed Janeiro 2016– 10…
Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger, Giuseppe Casalicchio + 6 more
Addressing Epistemic and Methodological Challenges of Experimentation Authors: ['Moritz Herrmann' 'F. Julian D. Lange' 'Katharina Eggensperger' 'Giuseppe Casalicchio' 'Marcel Wever' 'Matthias Feurer' 'David Rügamer' 'Eyke Hüllermeier' 'Anne‐Laure Boulesteix' 'Bernd Bischl'] We warn against a common but incomplete…
Brynne Gilmore
Realist evaluation, a methodology for exploring generative causation within complex health interventions to understand ‘how, why and for whom’ programmes work, is experiencing a surge of interest. Trends indicate that the proliferation in the use of this methodology also applies to research in low- and middle-income…
F. J. D. Lange, Juliane C. Wilcke, Sabine Hoffmann, Moritz Herrmann + 1 more
'Anne-Laure Boulesteix'] Empirical substantive research, such as in the life or social sciences, is commonly categorized into the two modes exploratory and confirmatory, both of which are essential to scientific progress. The former is also referred to as hypothesis-generating or data-contingent research, the latter is…
Authors not listed
This article proposes a three-level classification of artificial intelligence (AI) application in chemical sciences, reflecting the increasing degree of technology involvement in scientific and production processes: from automation of routine tasks (the level of "AI Assistant"), to the creation of specialized…
Authors not listed
Computational simulations of biomolecules provide a wealth of information about the thermodynamic landscape of biologically important systems, kinetics of important cellular processes, and the biophysical basis of life. Despite the ubiquity of molecular simulations in biophysical literature, major challenges persist…
Jagoda Głowacka-Walas, Kamil Sijko, Konrad Wojdan, Tomasz Gambin
Multi-omics analysis is increasingly popular in biomedical research. While promising, these analyses confront challenges in data integration, management, and interpretation due to their complexity, diversity, and volume. Moreover, achieving transparency, reproducibility, and repeatability in multi-omics analyses is…
Guy Schofield, Mariana Dittborn, Lucy Ellen Selman, Richard Huxtable
Background Despite its ubiquity in academic research, the phrase ‘ethical challenge(s)’ appears to lack an agreed definition. A lack of a definition risks introducing confusion or avoidable bias. Conceptual clarity is a key component of research, both theoretical and empirical. Using a rapid review methodology, we…
Anthony Sonrel, Almut Luetge, Charlotte Soneson, Izaskun Mallona + 16 more
Computational methods represent the lifeblood of modern molecular biology. Benchmarking is important for all methods, but with a focus here on computational methods, benchmarking is critical to dissect important steps of analysis pipelines, formally assess performance across common situations as well as edge cases, and…
Stéphane Cullati, Delphine S. Courvoisier, Angèle Gayet-Ageron, Guy Haller + 4 more
'Guy Haller' 'Olivier Irion' 'Thomas Agoritsas' 'Sandrine Rudaz' 'Thomas V. Perneger'] Background Many medical research projects encounter difficulties. The objective of this study was to assess the self-reported frequency of difficulties encountered by medical researchers while conducting research and to identify…
Barbora Rehák Bučková, Charlotte Fraza, Cecilie Koldbæk Lemvigh, Camilla Bärthel Flaaten + 11 more
Missing data remain a ubiquitous and critical challenge in large-scale clinical studies. Despite advances in imputation, most existing methods fail to address structured missingness, where data are missing according a deterministic pattern and which arise due to systematic patterns introduced by experimental design…
Maximilian M. Mandl, Frank Weber, Tobias Wöhrle, Anne-Laure Boulesteix
'Anne-Laure Boulesteix'] The term "researcher degrees of freedom" (RDF), which was introduced in metascientific literature in the context of the replication crisis in science, refers to the extent of flexibility a scientist has in making decisions related to data analysis. These choices occur at all stages of the data…
Xiaoqi Cabiria Liang, Nick Robertson, Marni Torkel, Sanghyun Kim + 3 more
The rapid growth of computational methods for the computational biology field highlights the critical role of benchmarking in guiding method selection. However, there is no standardised data structure that effectively links and stores datasets, performance metrics and available ground truth. Without such a unified and…
Authors not listed
Raman spectroscopy is an increasingly powerful and fast-growing analytical technique across diverse disciplines, from materials science and chemistry to biology and medicine, thanks to advances in Raman instrumentation and greatly supported by the flourishing of chemometrics and artificial intelligence (AI). However…
Authors not listed
Bonkowski and De Souza [Sol. Stat. Ionics 429, 116967 (2025)] provide a guide for performing molecular dynamics simulations of ion transport, including methods for estimating diffusion coefficients and their uncertainties from mean-squared displacement (MSD) data. The discussion of uncertainty in estimated diffusion…
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Artificial intelligence (AI) is reshaping scientific research by accelerating discovery and enabling the analysis of complex data that traditional methods struggle to handle. This review examines over 310,000 journal articles and patents from the CAS Content Collection (2015–2025), with a focus on, biomedical research…
James Maccarthy, Suzanne Guerin, Anthony G. Wilson, Emma R. Dorris
Involving patients in research broadens a researcher’s field of influence and may generate novel ideas. Preclinical research is integral to the progression of innovative healthcare. These are not patient-facing disciplines and implementing meaningful PPI can be a challenge. A discussion forum and thematic analysis…