Studies in health technology and informatics最新文献_第8页

Prognostic Value of Ceramide Dynamics in Patients with Acute Coronary Syndrome. 急性冠状动脉综合征患者神经酰胺动态变化的预后价值。

Studies in health technology and informatics Pub Date : 2024-11-22 DOI: 10.3233/SHTI241087

Elena Usova, Alexey Yakovlev, Georgy Kopanitsa, Oleg Metsker, Madina Alieva, Tatiana Makarova, Lev Malishevskii, Ekaterina Murashko, Elizaveta Kessenikh, Sergey Trusov, Asiiat Alieva, Alexandra Konradi

{"title":"Prognostic Value of Ceramide Dynamics in Patients with Acute Coronary Syndrome.","authors":"Elena Usova, Alexey Yakovlev, Georgy Kopanitsa, Oleg Metsker, Madina Alieva, Tatiana Makarova, Lev Malishevskii, Ekaterina Murashko, Elizaveta Kessenikh, Sergey Trusov, Asiiat Alieva, Alexandra Konradi","doi":"10.3233/SHTI241087","DOIUrl":"10.3233/SHTI241087","url":null,"abstract":"A dynamic study of ceramide concentrations and their association with recurrent event risk could enhance our understanding of cardiovascular complications. To assess the prognostic value of ceramide concentrations (Cer(d18:1/16:0), Cer(d18:1/18:0), Cer(d18:1/24:1), Cer(d18:1/24:0)) and their dynamics in combination with standard clinical and laboratory parameters and therapeutic interventions in ACS patients. Among 110 ACS patients, triple blood sampling was performed for targeted lipidomic analysis using high-performance liquid chromatography-tandem mass spectrometry. All ceramide concentrations peaked at admission and decreased by the 3rd day of hospitalization and at the 3-month follow-up. The difference between Cer(d18:1/18:0) concentration 3 months after hospital discharge and its baseline value on admission was strongly associated with recurrent events, independent of prior statin treatment. The association of the Cer(d18:1/18:0) change from 3rd day of hospitalization and its baseline concentration on admission with prognosis varied depending on the glycemic profile.","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"321 ","pages":"175-179"},"PeriodicalIF":0.0,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142690311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Extending the Scope of Telemedicine to Podiatric Medicine. 将远程医疗的范围扩大到足病医疗。

Studies in health technology and informatics Pub Date : 2024-11-22 DOI: 10.3233/SHTI241069

Lisa A Stojmanovski Mercieca, Cynthia Formosa, Nachiappan Chockalingam, Vincent Cassar

引用次数: 0

Use and Evaluation of GANs for Synthetic Data Generation in Pharmacogenetics. 在药物遗传学合成数据生成中使用和评估 GANs。

Studies in health technology and informatics Pub Date : 2024-11-22 DOI: 10.3233/SHTI241100

Dominic Aeschbacher, Jessica Meisner, Marko Miletic, Murat Sariyar

{"title":"Use and Evaluation of GANs for Synthetic Data Generation in Pharmacogenetics.","authors":"Dominic Aeschbacher, Jessica Meisner, Marko Miletic, Murat Sariyar","doi":"10.3233/SHTI241100","DOIUrl":"https://doi.org/10.3233/SHTI241100","url":null,"abstract":"Pharmacogenetics (PGx) explores the influence of genetic variability on drug efficacy and tolerability. Synthetic Data Generation (SDG) has emerged as a promising alternative to the labor-intensive process of collecting real-world PGx data, which is required for high-qualitative prediction models. This study investigates the performance of two Generative Adversarial Network (GAN) models, CTGAN and CTAB-GAN+, in generating synthetic PGx data. The benchmarking is based on utility metrics (Hellinger distance and Random Forest accuracy) and ϵ-identifiability. Results demonstrate that synthetic data generated by CTAB-GAN+ can surpass the original dataset in terms of utility. For instance, CTAB-GAN+ achieves higher Random Forest accuracy compared to the original data, indicating better predictive performance. These improvements suggest that synthetic data not only capture the essential patterns of the original data but also enhance model generalization and prediction capabilities, providing a more robust training ground for machine learning models. Consequently, SDG offers a promising solution to address data scarcity and imbalance in pharmacogenetic research.","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"321 ","pages":"240-244"},"PeriodicalIF":0.0,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142690234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Preparing for Hospital at Home: A Review of the Current Landscape of Training Practices. 在家为住院做准备：当前培训做法回顾。

Studies in health technology and informatics Pub Date : 2024-11-22 DOI: 10.3233/SHTI241060

Kerstin Denecke, Daniel Reichenpfader

{"title":"Preparing for Hospital at Home: A Review of the Current Landscape of Training Practices.","authors":"Kerstin Denecke, Daniel Reichenpfader","doi":"10.3233/SHTI241060","DOIUrl":"10.3233/SHTI241060","url":null,"abstract":"Hospital at Home (HaH) is a model of care that provides hospital-level care in the patient's home, requiring a unique set of competencies and skills from both multidisciplinary care teams and informal caregivers. These skills are often different from those required in traditional hospital settings. The aim of this paper is to consolidate the information of HaH-related education and training to support the development of standardized curricula to ensure safe hospitalization at home. We compiled relevant information from the scientific literature on HaH approaches and studies and conducted a web search. Our results indicate that healthcare professionals are trained in short training sessions, covering specific skills needed in the HaH context. These skills comprise, among others, communication, medication safety, infection control, and wound care. Patients and their families receive training in recognizing symptoms of deterioration and self-care. Concrete guidelines or standardized training programs are still missing. Future research should thus focus on developing standardized HaH training protocols and programs for both staff and patients to ensure patient safety at home.","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"321 ","pages":"48-52"},"PeriodicalIF":0.0,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142690309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mobile Health Technologies and Their Features Affecting Medication Adherence Among Cancer Patients: A Scoping Review. 影响癌症患者坚持用药的移动医疗技术及其特点：范围综述》。

Studies in health technology and informatics Pub Date : 2024-11-22 DOI: 10.3233/SHTI241064

Abdel Rahman Alsaify, Tourjana Islam Supti, Mahmood Alzubaidi, Mowafa Househ

引用次数: 0

Utilizing RAG and GPT-4 for Extraction of Substance Use Information from Clinical Notes. 利用 RAG 和 GPT-4 从临床笔记中提取药物使用信息。

Studies in health technology and informatics Pub Date : 2024-11-22 DOI: 10.3233/SHTI241070

Fatemeh Shah-Mohammadi, Joseph Finkelstein

引用次数: 0

A Novel Taxonomy for Navigating and Classifying Synthetic Data in Healthcare Applications. 医疗保健应用中合成数据导航和分类的新分类标准。

Studies in health technology and informatics Pub Date : 2024-11-22 DOI: 10.3233/SHTI241104

Bram van Dijk, Saif Ul Islam, Jim Achterberg, Hafiz Muhammad Waseem, Parisis Gallos, Gregory Epiphaniou, Carsten Maple, Marcel Haas, Marco Spruit

{"title":"A Novel Taxonomy for Navigating and Classifying Synthetic Data in Healthcare Applications.","authors":"Bram van Dijk, Saif Ul Islam, Jim Achterberg, Hafiz Muhammad Waseem, Parisis Gallos, Gregory Epiphaniou, Carsten Maple, Marcel Haas, Marco Spruit","doi":"10.3233/SHTI241104","DOIUrl":"https://doi.org/10.3233/SHTI241104","url":null,"abstract":"Data-driven technologies have improved the efficiency, reliability and effectiveness of healthcare services, but come with an increasing demand for data, which is challenging due to privacy-related constraints on sharing data in healthcare contexts. Synthetic data has recently gained popularity as potential solution, but in the flurry of current research it can be hard to oversee its potential. This paper proposes a novel taxonomy of synthetic data in healthcare to navigate the landscape in terms of three main varieties. Data Proportion comprises different ratios of synthetic data in a dataset and associated pros and cons. Data Modality refers to the different data formats amenable to synthesis and format-specific challenges. Data Transformation concerns improving specific aspects of a dataset like its utility or privacy with synthetic data. Our taxonomy aims to help researchers in the healthcare domain interested in synthetic data to grasp what types of datasets, data modalities, and transformations are possible with synthetic data, and where the challenges and overlaps between the varieties lie.","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"321 ","pages":"259-263"},"PeriodicalIF":0.0,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142690232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Leveraging Cancer Therapy Peptide Data: A Case Study on Machine Learning Application in Accelerating Cancer Research. 利用癌症治疗肽数据：加速癌症研究的机器学习应用案例研究》。

Studies in health technology and informatics Pub Date : 2024-11-22 DOI: 10.3233/SHTI241068

Georgios Feretzakis, Athanasios Anastasiou, Stavros Pitoglou, Aikaterini Sakagianni, Zoi Rakopoulou, Konstantinos Kalodanis, Vasileios Kaldis, Evgenia Paxinou, Dimitris Kalles, Vassilios S Verykios

引用次数: 0

Generative 3D Cardiac Shape Modelling for in-silico Trials. 生成三维心脏形状模型，用于样本内试验。

Studies in health technology and informatics Pub Date : 2024-11-22 DOI: 10.3233/SHTI241090

Andrei Gasparovici, Alex Serban

引用次数: 0

Using the German National Medication Plan for Clinical Studies in Practice-Based Research Networks. 在基于实践的研究网络中将德国国家用药计划用于临床研究。

Studies in health technology and informatics Pub Date : 2024-11-22 DOI: 10.3233/SHTI241082

Patrick Schmutz, Arthur Krauss, Sven Dörflinger, Arndt Becker, Andreas Polanc, Claudia Salm, Frank Peters-Klimm, Gudrun Hübner, Christian Erhardt, Christian Thies

{"title":"Using the German National Medication Plan for Clinical Studies in Practice-Based Research Networks.","authors":"Patrick Schmutz, Arthur Krauss, Sven Dörflinger, Arndt Becker, Andreas Polanc, Claudia Salm, Frank Peters-Klimm, Gudrun Hübner, Christian Erhardt, Christian Thies","doi":"10.3233/SHTI241082","DOIUrl":"10.3233/SHTI241082","url":null,"abstract":"The German National Medication Plan (GNMP) can be a valuable and interoperable data source for clinical studies, due to its digital specification and mandatory provisioning for chronically ill patients. Digital transfer of a patients current GNMP from the Patient Data Management System (PDMS) into electronic case report forms would avoid error prone manual data capturing. It is also essential for studies in practice-based research networks (PBRN), where data capturing must have as little impact as possible on everyday practice. The following issues are currently preventing seamless digital integration: There is no standardized interoperable export of the GNMP from PDMS. In the current form, pharmaceutical catalogs are needed to decode the contained pharmaceutical registration numbers. As accessibility to the pharmaceutical catalogs is restricted, there is no generic access to the actual information needed for study data evaluation. In order to conduct studies, feasible workarounds for these issues had to be implemented in the standard operating procedures, tools and participating GP practices. To overcome the GNMP's current lack of digital interoperability, the proposed solution combines semi-automated data export from PDMS at the GP practice and manual database search at the study center with a semi-automated processing pipeline to balance workload between GP practices, study management and evaluation.","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"321 ","pages":"150-154"},"PeriodicalIF":0.0,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142690244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0