Measuring Passenger Car Unit (PCU) at Four Legged Roundabout using Time Occupancy Data Collected from Drone by Sugiarto Sugiarto, Fadhlullah Apriandy, Ruhdi Faisal, Sofyan M. Saleh

“…This study aims to measure the values of passenger car unit (PCU) at a four-legged roundabout based on the time occupancy data in complex traffic operation. Within mixed traffic, the PCUs are needed as a equivalency factor to convert various type of vehicles to a standard unit. …”
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Assessment of soil classification based on cone penetration test data for Kaifeng area using optimized support vector machine by Hanliang Bian, Zhongxun Sun, Jiahan Bian, Zhaowei Qu, Jianwei Zhang, Xiangchun Xu

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Machine learning-based prediction of anxiety disorders using blood metabolite and social trait data from the UK Biobank by Annabel Smith, Jack J. Miller, Daniel C. Anthony, Daniel E. Radford-Smith

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On Explainability of Reinforcement Learning-Based Machine Learning Agents Trained with Proximal Policy Optimization That Utilizes Visual Sensor Data by Tomasz Hachaj, Marcin Piekarczyk

“…We publish all source codes so our experiments can be reproduced.…”
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visPIG--a web tool for producing multi-region, multi-track, multi-scale plots of genetic data. by Matthew Scales, Roland Jäger, Gabriele Migliorini, Richard S Houlston, Marc Y R Henrion

“…For sensitive data, the underlying R code can also be downloaded and run locally. visPIG is multi-track: it can display many different data types (e.g association, functional annotation, intensity, interaction, heat map data,…). …”
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Progression of Heart Failure in People with Type 2 Diabetes in Germany: An Analysis Using German Health Insurance Claims Data by Keni Cheng-Siang Lee, Tobias Wagner, Adee Kennedy, Michael Wilke

“…A model using coded data classified the patients with HF into ejection fraction (EF) categories. …”
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Identifying and characterising asthma subgroups at high risk of severe exacerbations using machine learning and longitudinal real-world data by Patrick Long, Andres Quintero, Javier Lopez-Molina, Merina Su, Nicola Boulter, Cindy Weber, Ralica Dimitrova

“…Objectives To identify and characterise distinct subgroups of patients with asthma with severe acute exacerbations (AEs) by using a multistep clustering methodology that combines supervised and unsupervised machine learning.Methods This cohort study used anonymised, all-payer medical and prescription US claim data from October 2015 to May 2022. First, gradient-boosted decision trees were trained to predict AE in 4 132 973 patients with asthma, of whom 86 735 experienced AE. …”
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Use of healthcare administrative claims data in observational studies of antirheumatic drug effects on pregnancy outcomes: A scoping review. by Shenthuraan Tharmarajah, Araniy Santhireswaran, Yasmeen Ameeriar, Lisa M McCarthy, Dharini Mahendira, Howard Berger, Mina Tadrous, Sara J T Guilcher

“…Of 14 studies reporting congenital anomalies, 12 (85.7%) specified ICD codes and 4 (28.6%) specified validated definitions for identification in claims data, the most of any reported adverse pregnancy outcome. …”
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DREAMS: A python framework for training deep learning models on EEG data with model card reporting for medical applications by Rabindra Khadka, Pedro G. Lind, Anis Yazidi, Asma Belhadi

“…However, most existing frameworks for EEG data analysis are either focused on preprocessing techniques or deep learning model development, often overlooking the crucial need for structured documentation and model interpretability. …”
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Barcode medication administration system use and safety implications: a data-driven longitudinal study supported by clinical observation by Kenneth K C Man, Ann Blandford, Rachel Williams, Yogini Jani, Kumud Kantilal

“…Regression models were applied to explore factors influencing medication scanning rates across wards of different specialties.Results Electronic data on 613 868 medication administrations showed overall medication scanning rates per ward ranged from 5.6% to 67% and patient scanning rates from 4.6% to 89%. …”
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OpenCyto: an open source infrastructure for scalable, robust, reproducible, and automated, end-to-end flow cytometry data analysis. by Greg Finak, Jacob Frelinger, Wenxin Jiang, Evan W Newell, John Ramey, Mark M Davis, Spyros A Kalams, Stephen C De Rosa, Raphael Gottardo

“…Pipelines are defined through a text-based csv file, limiting the need to write data-specific code, and are data agnostic to simplify repetitive analysis for core facilities. …”
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Development and validation of a distributed representation model of Japanese high-dimensional administrative claims data for clinical epidemiology studies by Hiroki Matsui, Kiyohide Fushimi, Hideo Yasunaga

“…We determined whether distributed representations can compress high-dimensional administrative claims data to adjust for unmeasured confounders. Method Using the Japanese Diagnosis Procedure Combination (DPC) database from 1291 hospitals (between April 2018 and March 2020), we applied the word2vec algorithm to create distributed representations for all medical codes. …”
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Patients potentially in need for palliative care in Germany—A regional small-area estimation based on death registry data by Daniela Gesell, Farina Hodiamont, Claudia Bausewein, Eva Grill, Daniela Koller

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lasertram: A Python library for time resolved analysis of laser ablation inductively coupled plasma mass spectrometry data by Jordan Lubbers, Adam J.R. Kent, Chris Russo

“…We outline its mathematical theory, code structure, and provide an example of how it can be used to provide the time resolved analysis necessitated by LA-ICP-MS data of complex geologic materials. …”
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Constipation among workers with depression/anxiety: a retrospective study using a claims database and survey data in Japan by Shin Fukudo, Kazutaka Nozawa, Yusuke Karasawa, Keisuke Nomoto

“…Objectives To investigate the prevalence, associated factors, treatment status and burden of constipation in workers with depression or anxiety.Study design This was a retrospective observational study using a pre-existing database.Setting Claims data from October to November 2022 and data from the survey conducted in November 2022 were extracted from the database.Participants This study included self-reported workers who completed the survey, after excluding those with major mental disorders diagnosed as distinct from depression or anxiety and constipation due to organic diseases identified by International Classification of Diseases (ICD-10) codes.Outcome measures The subjects were divided into three groups: treated depression/anxiety, untreated depression/anxiety and no depression/anxiety. …”
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Pretrained patient trajectories for adverse drug event prediction using common data model-based electronic health records by Junmo Kim, Joo Seong Kim, Ji-Hyang Lee, Min-Gyu Kim, Taehyun Kim, Chaeeun Cho, Rae Woong Park, Kwangsoo Kim

“…Abstract Background Pretraining electronic health record (EHR) data using language models has enhanced performance across various medical tasks. …”
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Information Needs for Opioid Use Disorder Treatment Using Buprenorphine Product: Qualitative Analysis of Suboxone-Focused Reddit Data by Madhusudan Basak, Omar Sharif, Sarah E Lord, Jacob T Borodovsky, Lisa A Marsch, Sandra A Springer, Edward V Nunes, Charles D Brackett, Luke J Archibald, Sarah M Preum

“…Following a standard protocol and guidance from clinical experts, we first identified 5 main themes from the data and then manually coded 6000 posts based on these themes. …”
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Evaluation of structured data from electronic health records to identify clinical classification criteria attributes for systemic lupus erythematosus by Rosalind Ramsey-Goldman, Theresa L Walunas, Abel N Kho, Anika S Ghosh, Jennifer A Pacheco, Vesna Mitrovic, Andy Wu, Kathryn L Jackson, Ryan Schusler, Anh Chung, Daniel Erickson, Karen Mancera-Cuevas, Yuan Luo

“…Individual criteria attribute and classification criteria algorithms as a whole were assessed over our combined cohorts and the overall performance of the algorithms was measured through sensitivity and specificity.Results Individual classification criteria attributes had a wide range of sensitivities, 7% (oral ulcers) to 97% (haematological disorders) and specificities, 56% (haematological disorders) to 98% (photosensitivity), but all could be identified in EHR data. In general, algorithms based on laboratory results performed better than those primarily based on diagnosis codes. …”
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Ankle Arthrodesis: Epidemiology, Etiology, and Complications in Diabetic vs Nondiabetic Patients Using US Nationwide Inpatient Sample Data by Assil Mahamid MD, David Maman MD, Summer Sofer, Mykhail Pavlenko MD, Amr Mansour MD, Marah Hodruj MD, Yaron Berkovich MD, Eyal Behrbalk MD

“…This study aims to compare the outcomes of AA in diabetic vs nondiabetic patients, using data from the Nationwide Inpatient Sample (NIS) from 2016 to 2019. …”
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Compliance of the management of hospitalized patients with heart failure with the quality criteria for health care: data from the St. Petersburg registry by G. V. Endubaeva, A. E. Solovyova, A. E. Medvedev, M. M. Kurbanova, E. I. Kogan, T. V. Gorbacheva, A. V. Yazenok, N. E. Zvartau, S. V. Villevalde

“…Hospitalizations of patients aged over 18 years with HF (ICD 10 code — I50.x) during the period from January 1, 2019 to October 1, 2020 were randomly selected from the "Chronic Heart Failure" registry of St. …”
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