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Harnessing Unstructured Data and Hospital Interoperability: The potential of next-generation platforms in transforming patient recruitment.

• Authors : Sundgren, Mats; Mistry, Rohit; Maeztu, Gabriel

Subjects: PATIENT selection; CLINICAL trials; DEEP learning

• Source: Applied Clinical Trials. Nov2024, Vol. 33 Issue 11, p12-17. 6p.

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Combining structured and unstructured data for predictive models: a deep learning approach.

• Authors : Zhang D; Department of Biomedical Informatics, The Ohio State University, 1800 Cannon Drive, Columbus, OH, 43210, USA.; School of Computer Science and Technology, Wuhan University of Technology, Wuhan, 430070, Hubei, China.

Subjects: Deep Learning* ; Machine Learning* ; Neural Networks, Computer*

• Source: BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2020 Oct 29; Vol. 20 (1), pp. 280. Date of Electronic Publication: 2020 Oct 29.Publisher: BioMed Central Country of Publication: England NLM ID: 101088682 Publication Model: Electronic Cited Medium: Internet ISSN: 1472-6947

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A Deep Learning-Based Framework for Offensive Text Detection in Unstructured Data for Heterogeneous Social Media

• Authors : Jamshid Bacha; Farman Ullah; Jebran Khan

Subjects: Cyberbully; unstructured data; deep learning

• Source: IEEE Access, Vol 11, Pp 124484-124498 (2023)

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Enhancing knowledge discovery from unstructured data using a deep learning approach to support subsurface modeling predictions

• Authors : Brendan Hoover; Dakota Zaengle; MacKenzie Mark-Moser

Subjects: subsurface; knowledge discovery (data mining); unstructured data

• Source: Frontiers in Big Data, Vol 6 (2023)

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Finding the best trade-off between performance and interpretability in predicting hospital length of stay using structured and unstructured data.

• Authors : Jaotombo, Franck^1,2 (AUTHOR) ; Adorni, Luca³ (AUTHOR); Ghattas, Badih⁴ (AUTHOR)

Subjects: *LENGTH of stay in hospitals; *DEEP learning; *TRANSFORMER models

• Source: PLoS ONE. 11/30/2023, Vol. 18 Issue 11, p1-22. 22p.

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A continuous convolutional trainable filter for modelling unstructured data.

• Authors : Coscia, Dario¹ (AUTHOR) ; Meneghetti, Laura¹ (AUTHOR); Demo, Nicola¹ (AUTHOR)

• Source: Computational Mechanics. Aug2023, Vol. 72 Issue 2, p253-265. 13p.

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Adding biological constraints to deep neural networks reduces their capacity tolearn unstructured data

• Authors : Tsvetkov, Christian; Malhotra, Gaurav; Evans, Benjamin D.

Subjects: deep learning; biological details; memorization

• Source: Proceedings of the Annual Meeting of the Cognitive Science Society. 42

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Vector databases for unstructured data processing

• Authors : Blašković, Luka; Oreški, Goran

Subjects: Milvus.io; Artificial intelligence; informacijski sustavi

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Primjena strojnog učenja u klasifikaciji slika kao tipičnih primjera nestrukturiranih tipova podataka ; Application of machine learning on the classification of images as typical examples of unstructured data types

• Authors : Ivandić, Tomislav; Panjkota, Ante

Subjects: strojno učenje; duboko učenje; klasifikacija slika

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Unbox the Black-Box: Predict and Interpret YouTube Viewership Using Deep Learning.

• Authors : Xie, Jiaheng (AUTHOR); Chai, Yidong (AUTHOR); Liu, Xiao (AUTHOR)

Subjects: DEEP learning; VIDEO production & direction; PREDICTION models

• Source: Journal of Management Information Systems. 2023, Vol. 40 Issue 2, p541-579. 39p. 1 Diagram, 16 Charts, 6 Graphs.

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