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11 Publications visible to you, out of a total of 11
BioModelsML: Building a FAIR and reproducible collection of machine learning models in life sciences and medicine for easy reuse

Abstract (Expand)

Abstract Machine learning (ML) models are widely used in life sciences and medicine; however, they are scattered across various platforms and there are several challenges that hinder their accessibility, …r their accessibility, reproducibility and reuse. In this manuscript, we present the formalisation and pilot implementation of community protocol to enable FAIReR (Findable, Accessible, Interoperable, Reusable, and Reproducible) sharing of ML models. The protocol consists of eight steps, including sharing model training code, dataset information, reproduced figures, model evaluation metrics, trained models, Dockerfiles, model metadata, and FAIR dissemination. Applying these measures we aim to build and share a comprehensive public collection of FAIR ML models in the BioModels repository through incentivized community curation. In a pilot implementation, we curated diverse ML models to demonstrate the feasibility of our approach and we discussed the current challenges. Building a FAIReR collection of ML models will directly enhance the reproducibility and reusability of ML models, minimising the effort needed to reimplement models, maximising the impact on the application and significantly accelerating the advancement in the field of life science and medicine.

Authors: Divyang Deep Tiwari, Nils Hoffmann, Kieran Didi, Sumukh Deshpande, Sucheta Ghosh, Tung V. N. Nguyen, Karthik Raman, Henning Hermjakob, Rahuman Sheriff

Date Published: 23rd May 2023

Publication Type: Misc

Horizons: nuclear astrophysics in the 2020s and beyond

Abstract (Expand)

Abstract Nuclear astrophysics is a field at the intersection of nuclear physics and astrophysics, which seeks to understand the nuclear engines of astronomical objects and the origin of the chemical …the origin of the chemical elements. This white paper summarizes progress and status of the field, the new open questions that have emerged, and the tremendous scientific opportunities that have opened up with major advances in capabilities across an ever growing number of disciplines and subfields that need to be integrated. We take a holistic view of the field discussing the unique challenges and opportunities in nuclear astrophysics in regards to science, diversity, education, and the interdisciplinarity and breadth of the field. Clearly nuclear astrophysics is a dynamic field with a bright future that is entering a new era of discovery opportunities.

Authors: H Schatz, A D Becerril Reyes, A Best, E F Brown, K Chatziioannou, K A Chipps, C M Deibel, R Ezzeddine, D K Galloway, C J Hansen, F Herwig, A P Ji, M Lugaro, Z Meisel, D Norman, J S Read, L F Roberts, A Spyrou, I Tews, F X Timmes, C Travaglio, N Vassh, C Abia, P Adsley, S Agarwal, M Aliotta, W Aoki, A Arcones, A Aryan, A Bandyopadhyay, A Banu, D W Bardayan, J Barnes, A Bauswein, T C Beers, J Bishop, T Boztepe, B Côté, M E Caplan, A E Champagne, J A Clark, M Couder, A Couture, S E de Mink, S Debnath, R J deBoer, J den Hartogh, P Denissenkov, V Dexheimer, I Dillmann, J E Escher, M A Famiano, R Farmer, R Fisher, C Fröhlich, A Frebel, C Fryer, G Fuller, A K Ganguly, S Ghosh, B K Gibson, T Gorda, K N Gourgouliatos, V Graber, M Gupta, W C Haxton, A Heger, W R Hix, W C G Ho, E M Holmbeck, A A Hood, S Huth, G Imbriani, R G Izzard, R Jain, H Jayatissa, Z Johnston, T Kajino, A Kankainen, G G Kiss, A Kwiatkowski, M La Cognata, A M Laird, L Lamia, P Landry, E Laplace, K D Launey, D Leahy, G Leckenby, A Lennarz, B Longfellow, A E Lovell, W G Lynch, S M Lyons, K Maeda, E Masha, C Matei, J Merc, B Messer, F Montes, A Mukherjee, M R Mumpower, D Neto, B Nevins, W G Newton, L Q Nguyen, K Nishikawa, N Nishimura, F M Nunes, E O’Connor, B W O’Shea, W-J Ong, S D Pain, M A Pajkos, M Pignatari, R G Pizzone, V M Placco, T Plewa, B Pritychenko, A Psaltis, D Puentes, Y-Z Qian, D Radice, D Rapagnani, B M Rebeiro, R Reifarth, A L Richard, N Rijal, I U Roederer, J S Rojo, J S K, Y Saito, A Schwenk, M L Sergi, R S Sidhu, A Simon, T Sivarani, Á Skúladóttir, M S Smith, A Spiridon, T M Sprouse, S Starrfield, A W Steiner, F Strieder, I Sultana, R Surman, T Szücs, A Tawfik, F Thielemann, L Trache, R Trappitsch, M B Tsang, A Tumino, S Upadhyayula, J O Valle Martínez, M Van der Swaelmen, C Viscasillas Vázquez, A Watts, B Wehmeyer, M Wiescher, C Wrede, J Yoon, R G T Zegers, M A Zermane, M Zingale

Date Published: 15th Nov 2022

Publication Type: Journal

Towards Effortless Navigation of Scientific-Literature Screen Reading for Biocuration

Abstract

Not specified

Authors: Sucheta Ghosh, Wolfgang Müller, Ulrike Wittig, Maja Rey

Date Published: 5th May 2022

Publication Type: InProceedings

The Effect of an Additional Structured Methods Presentation on Decision-Makers' Reading Time and Opinions on the Helpfulness of the Methods in a Quantitative Report: Nonrandomized Trial.

Abstract (Expand)

BACKGROUND: Although decision-makers in health care settings need to read and understand the validity of quantitative reports, they do not always carefully read information on research methods. Presenting … the methods in a more structured way could improve the time spent reading the methods and increase the perceived relevance of this important report section. OBJECTIVE: To test the effect of a structured summary of the methods used in a quantitative data report on reading behavior with eye-tracking and measure the effect on the perceived importance of this section. METHODS: A nonrandomized pilot trial was performed in a computer laboratory setting with advanced medical students. All participants were asked to read a quantitative data report; an intervention arm was also shown a textbox summarizing key features of the methods used in the report. Three data-collection methods were used to document reading behavior and the views of participants: eye-tracking (during reading), a written questionnaire, and a face-to-face interview. RESULTS: We included 35 participants, 22 in the control arm and 13 in the intervention arm. The overall time spent reading the methods did not differ between the 2 arms. The intervention arm considered the information in the methods section to be less helpful for decision-making than did the control arm (scores for perceived helpfulness were 4.1 and 2.9, respectively, range 1-10). Participants who read the box more intensively tended to spend more time on the methods as a whole (Pearson correlation 0.81, P=.001). CONCLUSIONS: Adding a structured summary of information on research methods attracted attention from most participants, but did not increase the time spent on reading the methods or lead to increased perceptions that the methods section was helpful for decision-making. Participants made use of the summary to quickly judge the methods, but this did not increase the perceived relevance of this section.

Authors: J. Koetsenruijter, P. Wronski, S. Ghosh, W. Muller, M. Wensing

Date Published: 12th Apr 2022

Publication Type: Journal

Use of a quantitative data report in a hypothetical decision scenario for health policymaking: a computer-assisted laboratory study

Abstract (Expand)

Background: Quantitative data reports are widely produced to inform health policy decisions. Policymakers are expected to critically assess provided information in order to incorporate the best available … evidence into the decision-making process. Many other factors are known to influence this process, but little is known about how quantitative data reports are actually read. We explored the reading behavior of (future) health policy decision-makers, using innovative methods. Methods: We conducted a computer-assisted laboratory study, involving starting and advanced students in medicine and health sciences, and professionals as participants. They read a quantitative data report to inform a decision on the use of resources for long-term care in dementia in a hypothetical decision scenario. Data were collected through eye-tracking, questionnaires, and a brief interview. Eye-tracking data were used to generate ‘heatmaps’ and five measures of reading behavior. The questionnaires provided participants’ perceptions of understandability and helpfulness as well as individual characteristics. Interviews documented reasons for attention to specific report sections. The quantitative analysis was largely descriptive, complemented by Pearson correlations. Interviews were analyzed by qualitative content analysis. Results: In total, 46 individuals participated [students (85%), professionals (15%)]. Eye-tracking observations showed that the participants spent equal time and attention for most parts of the presented report, but were less focused when reading the methods section. The qualitative content analysis identified 29 reasons for attention to a report section related to four topics. Eye-tracking measures were largely unrelated to participants’ perceptions of understandability and helpfulness of the report. Conclusions: Eye-tracking data added information on reading behaviors that were not captured by questionnaires or interviews with health decision-makers.

Authors: Pamela Wronski, Michel Wensing, Sucheta Ghosh, Lukas Gärttner, Wolfgang Müller, Jan Koetsenruijter

Date Published: 1st Dec 2021

Publication Type: Journal

Combining dictionary- and rule-based approximate entity linking with tuned BioBERT

Abstract (Expand)

Chemical named entity recognition (NER) is a significant step for many downstream applications like entity linking for the chemical text-mining pipeline. However, the identification of chemical entities … in a biomedical text is a challenging task due to the diverse morphology of chemical entities and the different types of chemical nomenclature. In this work, we describe our approach that was submitted for BioCreative version 7 challenge Track 2, focusing on the ‘Chemical Identification’ task for identifying chemical entities and entity linking, using MeSH. For this purpose, we have applied a two-stage approach as follows (a) usage of fine-tuned BioBERT for identification of chemical entities (b) semantic approximate search in MeSH and PubChem databases for entity linking. There was some friction between the two approaches, as our rule-based approach did not harmonise optimally with partially recognized words forwarded by the BERT component. For our future work, we aim to resolve the issue of the artefacts arising from BERT tokenizers and develop joint learning of chemical named entity recognition and entity linking using pre-trained transformer-based models and compare their performance with our preliminary approach. Next, we will improve the efficiency of our approximate search in reference databases during entity linking. This task is non-trivial as it entails determining similarity scores of large sets of trees with respect to a query tree. Ideally, this will enable flexible parametrization and rule selection for the entity linking search.

Authors: Ghadeer Mobasher, Lukrécia Mertová, Sucheta Ghosh, Olga Krebs, Bettina Heinlein, Wolfgang Müller

Date Published: 11th Nov 2021

Publication Type: Proceedings

Watching people decide: decision prediction using heatmaps of reading of a decision-support document

Abstract

Not specified

Authors: Sucheta Ghosh, Pamela Wronski, Jan Koetsenruijter, Wolfgang Mueller, Michel Wensing

Date Published: 27th Sep 2021

Publication Type: Journal

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