Hierarchical embedding attention for overall survival prediction in lung cancer from unstructured EHRs by Domenico Paolo, Carlo Greco, Alessio Cortellini, Sara Ramella, Paolo Soda, Alessandro Bria, Rosa Sicilia

“…Natural Language Processing (NLP), particularly Named Entity Recognition (NER), has been instrumental in extracting structured information from EHR data. However, existing literature primarly focuses on extracting handcrafted clinical features through NLP and NER methods without delving into their learned representations. …”
Get full text

Using large language models to extract plant functional traits from unstructured text by Viktor Domazetoski, Holger Kreft, Helena Bestova, Philipp Wieder, Radoslav Koynov, Alireza Zarei, Patrick Weigelt

Get full text

Combining Topic Modeling, Sentiment Analysis, and Corpus Linguistics to Analyze Unstructured Web-Based Patient Experience Data: Case Study of Modafinil Experiences by Julia Walsh, Jonathan Cave, Frances Griffiths

“…ObjectiveThe study aims to (1) investigate how combining unsupervised natural language processing (NLP) and corpus linguistics can explore patient perspectives from a large unstructured dataset of modafinil experiences, (2) compare findings with Cochrane meta-analyses on modafinil’s effectiveness, and (3) develop a methodology for analyzing such data. …”
Get full text

Research on real-world knowledge mining and knowledge graph completion (II): Methods and pro-gress of information extraction from unstructured electronic medical records by Si-Yu YAN, Xu-Hui LI, Mu-Kun CHEN, Hai-Feng ZHU, Jie-Jun TAN, Kuang GAO, Yong-Bo WANG, Qiao HUANG, Xiang-Ying REN, Ying-Hui JIN, Xing-Huan WANG

Subjects: “…unstructured data…”
Get full text

Extracting Information from Unstructured Medical Reports Written in Minority Languages: A Case Study of Finnish by Elisa Myllylä, Pekka Siirtola, Antti Isosalo, Jarmo Reponen, Satu Tamminen, Outi Laatikainen

“…With this approach, unstructured information could be transformed into a structured format. …”
Get full text

Unstructured road semantic segmentation method based on 3D point cloud of open pit mine by Caiwu LU, Jianan XUE, Meng LI, Shengyu YAN, sai ZHANG, Song JIANG, Runfeng HE

“…Compared with urban structured roads, unstructured roads in open pit mining scenarios are characterized by fuzzy road and terrain boundary features, no obvious road edges, and large spatial 3D coordinate spans. …”
Get full text

Vision-Based Branch Road Detection for Intersection Navigation in Unstructured Environment Using Multi-Task Network by Joonwoo Ahn, Yangwoo Lee, Minsoo Kim, Jaeheung Park

“…Autonomous vehicles need a driving method to be less dependent on localization data to navigate intersections in unstructured environments because these data may not be accurate in such environments. …”
Get full text

Collision Detection Algorithms for Autonomous Loading Operations of LHD-Truck Systems in Unstructured Underground Mining Environments by Mingyu Lei, Pingan Peng, Liguan Wang, Yongchun Liu, Ru Lei, Chaowei Zhang, Yongqing Zhang, Ya Liu

Get full text

Automated Extraction of Stroke Severity From Unstructured Electronic Health Records Using Natural Language Processing by Marta Fernandes, M. Brandon Westover, Aneesh B. Singhal, Sahar F. Zafar

Get full text

Diagnosis extraction from unstructured Dutch echocardiogram reports using span- and document-level characteristic classification by Bauke Arends, Melle Vessies, Dirk van Osch, Arco Teske, Pim van der Harst, René van Es, Bram van Es

“…For settings with limited training data, SetFit may be a promising alternative for document classification. …”
Get full text

Convergence Analysis on Unstructured Meshes of a DDFV Method for Flow Problems with Full Neumann Boundary Conditions by A. Kinfack Jeutsa, A. Njifenjou, J. Nganhou

“…A Discrete Duality Finite Volume (DDFV) method to solve on unstructured meshes the flow problems in anisotropic nonhomogeneous porous media with full Neumann boundary conditions is proposed in the present work. …”
Get full text

An automated information extraction model for unstructured discharge letters using large language models and GPT-4 by Robert M. Siepmann, Giulia Baldini, Cynthia S. Schmidt, Daniel Truhn, Gustav Anton Müller-Franzes, Amin Dada, Jens Kleesiek, Felix Nensa, René Hosch

Get full text

Extracting Cognitive Impairment Assessment Information From Unstructured Notes in Electronic Health Records Using Natural Language Processing Tools: Validation with Clinical Assessment Data by Wang KY, Mahesri M, Novoa-Laurentiev J, Bessette LG, York C, Zakoul H, Lee SB, Ngan K, Zhou L, Kim DH, Lin KJ

“…We applied an NLP approach to identify the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE) scores from unstructured clinician notes in EHR. Using the NLP-extracted MoCA or MMSE scores from EHR, we compared mean differences of extracted MoCA or MMSE by cognition status determined by MDS (impaired vs intact cognition) and OASIS (severe impairment vs intact cognition) data, respectively.Results: Our study cohort had 7419 patients who had MDS (19.7%) or OASIS (80.3%) assessments, with a mean age of 80 (SD=7) years and 60% female. …”
Get full text

Structured digital tables on the Semantic Web: toward a structured digital literature by Kei‐Hoi Cheung, Matthias Samwald, Raymond K Auerbach, Mark B Gerstein

Get full text

Unifying Structured Data as Graph for Data-to-Text Pre-Training by Shujie Li, Liang Li, Ruiying Geng, Min Yang, Binhua Li, Guanghu Yuan, Wanwei He, Shao Yuan, Can Ma, Fei Huang, Yongbin Li

Get full text

Cardinality-constrained structured data-fitting problems by Fan, Zhenan, Fang, Huang, Friedlander, Michael P.

“…A memory-efficient solution framework is proposed for the cardinality-constrained structured data-fitting problem. Dual-based atom-identification rules reveal the structure of the optimal primal solution from near-optimal dual solutions, which allows for a simple and computationally efficient algorithm that translates any feasible dual solution into a primal solution satisfying the cardinality constraint. …”
Get full text

Three-Way Merging Algorithm for Structured Data by Jan Janech, Patrik Hrkut, Matej Mesko, Marek Tavac

“…Since the diff3 algorithm is designed only for merging text files, we had to change it to enable data merging at the level of programming structures. …”
Get full text

T2F: a domain-agnostic multi-agent framework for unstructured text to factuality evaluation items generation by Xin Tong, Jingya Wang, Yasen Aizezi, Hanming Zhai, Bo Jin

“…The generated data effectively assess LLMs’ factuality accuracy, highlighting T2F’s capability as a scalable and domain-agnostic factuality evaluation framework.…”
Get full text

Natural Language Processing framework for identifying abdominal aortic aneurysm repairs using unstructured electronic health records by Daniel C. Thompson, Reza Mofidi

“…Abstract Patient identification for national registries often relies upon clinician recognition of cases or retrospective searches using potentially inaccurate clinical codes, leading to incomplete data capture and inefficiencies. Natural Language Processing (NLP) offers a promising solution by automating analysis of electronic health records (EHRs). …”
Get full text

The Hybrid Market Segmentation of Electric Vehicles in Ukraine Using Data Science Methods by Andrusyk Yevhenii V., Guryanova Lidiya S.

Subjects: Get full text