JCO Clinical Cancer Informatics最新文献

{"title":"Predictive Model of Acute Rectal Toxicity in Prostate Cancer Treated With Radiotherapy.","authors":"Keyur D Shah, Beow Y Yeap, Hoyeon Lee, Zainab O Soetan, Maryam Moteabbed, Stacey Muise, Jessica Cowan, Kyla Remillard, Brenda Silvia, Nancy P Mendenhall, Edward Soffen, Mark V Mishra, Sophia C Kamran, David T Miyamoto, Harald Paganetti, Jason A Efstathiou, Ibrahim Chamseddine","doi":"10.1200/CCI-24-00252","DOIUrl":"https://doi.org/10.1200/CCI-24-00252","url":null,"abstract":"<p><strong>Purpose: </strong>To aid personalized treatment selection, we developed a predictive model for acute rectal toxicity in patients with prostate cancer undergoing radiotherapy with photons and protons.</p><p><strong>Materials and methods: </strong>We analyzed a prospective multi-institutional cohort of 278 patients treated from 2012 to 2023 across 10 centers. Dosimetric and nondosimetric variables were collected, and key predictors were identified using purposeful feature selection. The cohort was split into discovery (n = 227) and validation (n = 51) data sets. The dose along the rectum surface was transformed into a two-dimensional surface, and dose-area histograms (DAHs) were quantified. A convolutional neural network (CNN) was developed to extract dosimetric features from the DAH and integrate them with nondosimetric predictors. Model performance was benchmarked against logistic regression (LR) using the AUC.</p><p><strong>Results: </strong>Key predictors included rectum length, race, age, and hydrogel spacer use. The CNN model demonstrated stability in the discovery data set (AUC = 0.81 ± 0.11) and outperformed LR in the validation data set (AUC = 0.81 <i>v</i> 0.54). Separate analysis of photon and proton subsets yielded consistent AUCs of 0.7 and 0.92, respectively. In the photon high-risk group, the model achieved 83% sensitivity, and in proton subsets, it achieved 100% sensitivity and specificity, indicating the potential to be used for treatment selection in these patients.</p><p><strong>Conclusion: </strong>Our novel approach effectively predicts rectal toxicity across photon and proton subsets, demonstrating the utility of integrating dosimetric and nondosimetric features. The model's strong performance across modalities suggests potential for guiding treatment decisions, warranting prospective validation.</p>","PeriodicalId":51626,"journal":{"name":"JCO Clinical Cancer Informatics","volume":"9 ","pages":"e2400252"},"PeriodicalIF":3.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665355","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}

{"title":"Methodologic Approach to Defining Comorbidities in a Cohort of Patients With Cancer: An Example in the Optimal Breast Cancer Chemotherapy Dosing Study.","authors":"Peng Wang, Kelli O'Connell, Jenna Bhimani, Victoria Blinder, Rachael Burganowski, Isaac J Ergas, Grace B Gallagher, Jennifer J Griggs, Narre Heon, Tatjana Kolevska, Yuriy Kotsurovskyy, Candyce H Kroenke, Cecile A Laurent, Raymond Liu, Kanichi G Nakata, Sonia Persaud, Donna R Rivera, Janise M Roh, Sara Tabatabai, Emily Valice, Elisa V Bandera, Lawrence H Kushi, Erin J Aiello Bowles, Elizabeth D Kantor","doi":"10.1200/CCI-24-00231","DOIUrl":"10.1200/CCI-24-00231","url":null,"abstract":"<p><strong>Purpose: </strong>We evaluated the definitions of five comorbidities (renal and hepatic impairments, anemia, neutropenia, and thrombocytopenia) in women with breast cancer using data from electronic health records.</p><p><strong>Methods: </strong>In 11,097 women receiving adjuvant chemotherapy for stage I-IIIA breast cancer at Kaiser Permanente Northern California or Kaiser Permanente Washington, we assessed comorbidity definitions in two commonly used lookback windows (1 year before diagnosis, T1; and extending until chemotherapy initiation, T1-2). Within each, we assessed data availability and agreement between International Classification of Diseases (ICD)-defined and lab-defined comorbidities of varying severity. To assess how different pieces of information may affect providers in making treatment decisions, we used multivariable logistic regression to evaluate four-category (with comorbidity indicated by both ICD and lab, ICD-only, lab-only, or neither) and collapsed binary (comorbidity indicated by either ICD or lab <i>v</i> neither) definitions in relation to first cycle chemotherapy dose reduction (FCDR).</p><p><strong>Results: </strong>Extending the lookback period to chemotherapy initiation increased laboratory data availability (missingness ≤4.1% in T1-2 <i>v</i> >40% in T1). Assessment of agreement guided selection of laboratory cutpoints. In both time periods, the four-category and binary comorbidity variables were associated with use of FCDR, but binary variables had larger cell sizes and more stability of regression models. Ultimately, the comorbidity variables in T1 were defined by a combination of either ICD/qualifying laboratory values. Results were similar in T1-2, except laboratory data alone outperformed the combination variable for renal and hepatic comorbidity.</p><p><strong>Conclusion: </strong>Leveraging both ICD and lab data and extending the lookback period to include postdiagnosis but prechemotherapy initiation may provide better capture of comorbidity. Future studies may consider validating our findings with a gold-standard comorbidity status and in other community health care settings.</p>","PeriodicalId":51626,"journal":{"name":"JCO Clinical Cancer Informatics","volume":"9 ","pages":"e2400231"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11839177/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143417054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Erratum: Automated Electronic Health Record Data Extraction and Curation Using ExtractEHR.","authors":"Tamara P Miller, Kelly D Getz, Edward Krause, Yun Gun Jo, Sandhya Charapala, M Monica Gramatges, Karen Rabin, Michael E Scheurer, Jennifer J Wilkes, Brian T Fisher, Richard Aplenc","doi":"10.1200/CCI-25-00013","DOIUrl":"https://doi.org/10.1200/CCI-25-00013","url":null,"abstract":"","PeriodicalId":51626,"journal":{"name":"JCO Clinical Cancer Informatics","volume":"9 ","pages":"e2500013"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143442954","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}

{"title":"CFO: Calibration-Free Odds Bayesian Designs for Dose Finding in Clinical Trials.","authors":"Jialu Fang, Ninghao Zhang, Wenliang Wang, Guosheng Yin","doi":"10.1200/CCI-24-00184","DOIUrl":"10.1200/CCI-24-00184","url":null,"abstract":"<p><strong>Purpose: </strong>Calibration-free odds type (CFO-type) designs have been demonstrated to be robust, model-free, and practically useful, which have become the state-of-the-art approach for dose finding. However, a key challenge for implementing such designs is a lack of accessible tools. We develop a user-friendly <i>R</i> package and <i>Shiny</i> web-based software to facilitate easy implementation of CFO-type designs. Moreover, we incorporate randomization into the CFO framework.</p><p><strong>Methods: </strong>We created the <i>R</i> package CFO and leveraged <i>R Shiny</i> to build an interactive web application, CFO suite, for implementing CFO-type designs. We introduce the randomized CFO (rCFO) design by integrating the exploration-exploitation mechanism into the CFO framework.</p><p><strong>Results: </strong>The CFO package and CFO suite encompass various variants tailored to different clinical settings. Beyond the fundamental CFO design, these include the two-dimensional CFO (2dCFO) for drug-combination trials, accumulative CFO (aCFO) for accommodating all dose information, rCFO for integrating exploration-exploitation via randomization, time-to-event CFO (TITE-CFO), and fractional CFO (fCFO) for addressing late-onset toxicity. Using all information and addressing delayed toxicity outcomes, TITE-aCFO and fractional-aCFO are also included. The package provides functions for determining the subsequent cohort dose, selecting the maximum tolerated dose, and conducting simulations to evaluate performance, with results presented through textual and graphical outputs.</p><p><strong>Conclusion: </strong>The CFO package and CFO suite provide comprehensive and flexible tools for implementing CFO-type designs in phase I clinical trials. This work is highly significant as it integrates all existing CFO-type designs to facilitate novel trial designs with enhanced performance. In addition, this promotes the spread of statistical methods using a user-friendly <i>R</i> package and <i>Shiny</i> software. It strengthens collaborations between biostatisticians and clinicians, further enhancing trial performance in terms of efficiency and accuracy.</p>","PeriodicalId":51626,"journal":{"name":"JCO Clinical Cancer Informatics","volume":"9 ","pages":"e2400184"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11797228/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143071238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Technology on Quality of Thoracic Multidisciplinary Cancer Conferences.","authors":"Opuruiche Ibekwe, Carmelo Gaudioso, Kristopher M Attwood, Saraswati Pokharel, Charles L Roche, Chukwumere E Nwogu","doi":"10.1200/CCI-24-00156","DOIUrl":"https://doi.org/10.1200/CCI-24-00156","url":null,"abstract":"<p><strong>Purpose: </strong>Complex cancers require discussion at multidisciplinary cancer conferences (MCCs) to determine the best management. This study assessed the impact of a tumor board (TB)-specific information technology platform on the quality of information presented, case discussions, and care plans at thoracic MCCs.</p><p><strong>Methods: </strong>Between September 2020 and February 2022, using a before-after study design, we prospectively collected data through direct observation of thoracic MCCs at an academic cancer center. In addition, we reviewed medical records to assess the rate of change in care plans, compliance of all care plans with national guidelines, concordance of treatment received with MCC recommendations, and time from MCC presentation to treatment. Observational data were collected using a validated tool, Metric for the Observation of Decision-Making. We used SAS version 9.4 (SAS Institute Inc, Cary, NC) for statistical analyses.</p><p><strong>Results: </strong>We identified 151 and 166 thoracic cancer cases before and after implementation of the information technology platform, respectively. The overall quality of case presentation and discussion, represented by a mean composite score (summation of individual variables scored on a 1-5 scale, poor to excellent), increased from 56.8 to 82.0 (<i>P</i> < .001). This improvement was also observed across multiple subcomponents of the composite score all with <i>P</i> < .001. There was no statistically significant difference between the two cohorts in rate of change in care plans by the MCC, care plan compliance with national guidelines, and concordance of treatment received with MCC recommendations.</p><p><strong>Conclusion: </strong>Technology improves the quality of information and discussion at TBs. However, this study did not demonstrate an impact on compliance with practice guidelines. Practitioners should explore the available TB technology platforms to optimize the conduct of MCCs in their respective institutions.</p>","PeriodicalId":51626,"journal":{"name":"JCO Clinical Cancer Informatics","volume":"9 ","pages":"e2400156"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143517266","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}

{"title":"Erratum: Identification of Novel DNA Methylation Prognostic Biomarkers for AML With Normal Cytogenetics.","authors":"Cândida Cardoso, Daniel Pestana, Sreemol Gokuladhas, Ana D Marreiros, Justin M O'Sullivan, Alexandra Binnie, Mónica Teotónio Fernandes, Pedro Castelo-Branco","doi":"10.1200/CCI-25-00012","DOIUrl":"https://doi.org/10.1200/CCI-25-00012","url":null,"abstract":"","PeriodicalId":51626,"journal":{"name":"JCO Clinical Cancer Informatics","volume":"9 ","pages":"e2500012"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143442955","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}

{"title":"Prognosis of p16 and Human Papillomavirus Discordant Oropharyngeal Cancers and the Exploration of Using Natural Language Processing to Analyze Free-Text Pathology Reports.","authors":"Ethan Shin, Justin Choi, Tony K W Hung, Chester Poon, Nadeem Riaz, Yao Yu, Jung Julie Kang","doi":"10.1200/CCI-24-00177","DOIUrl":"https://doi.org/10.1200/CCI-24-00177","url":null,"abstract":"<p><strong>Purpose: </strong>Treatment deintensification for human papillomavirus-positive (HPV+)-associated oropharyngeal cancer (OPC) has been the catalyst of experts worldwide. In situ hybridization is optimal to identify HPV+ OPC, but immunohistochemistry for its surrogate p16INK4a (p16) is standard-of-care given its availability and sensitivity. HPV testing is not required for clinical management, so treatments are often administered on the basis of p16 status alone. However, the prognosis of p16/HPV discordant tumors is uncertain.</p><p><strong>Materials and methods: </strong>This cohort study included 727 consecutive patients with OPC with digitized unstructured pathology reports receiving curative radiation therapy at an academic cancer center. Natural language processing (NLP) methods were used to classify biomarker status and compared against manually derived classification. Patients were excluded if either p16 or HPV testing was not performed or equivocal. Primary end points were progression-free survival (PFS), cancer-specific survival (CSS), and overall survival.</p><p><strong>Results: </strong>NLP classified p16 and HPV status from a majority (91%) of reports. Accuracy, positive predictive value, sensitivity, and <i>F</i>-score for NLP-derived p16/HPV were 84%/82%, 91%/87%, 90%/89%, and 90%/88%, respectively. Four groups were identified: p16-positive (p16+)/HPV+ (75%), p16+/HPV-negative (HPV-; 13%), p16-negative (p16-)/HPV- (10%), and p16-/HPV+ (2%). There was no statistically significant difference in outcomes between p16+/HPV- and p16-/HPV- patients (5-year PFS 76.1% <i>v</i> 68.9%; <i>P</i> = .12; 5-year CSS 81.5% <i>v</i> 84.9%; <i>P</i> = .22). Number needed to harm calculations estimated one excess cancer-related death for every 10 p16+/HPV- patients, compared with that expected with p16+/HPV+ patients.</p><p><strong>Conclusion: </strong>NLP classified head and neck cancer pathology reports with high concordance with gold-standard categorization, but a conspicuous portion of reports could not be interpreted. p16/HPV discordant OPC constitutes a noteworthy minority of patients. The inferior prognosis of p16+/HPV- suggests that p16 alone for prognostication is insufficient-especially when considering treatment de-escalation.</p>","PeriodicalId":51626,"journal":{"name":"JCO Clinical Cancer Informatics","volume":"9 ","pages":"e2400177"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143450861","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}

{"title":"Incorporating Structured and Unstructured Data Sources to Identify and Characterize Hereditary Cancer Testing Among Veterans With Metastatic Castration-Resistant Prostate Cancer.","authors":"Danielle Candelieri-Surette, Anna Hung, Fatai Y Agiri, Mengke Hu, Elizabeth E Hanchrow, Kyung Min Lee, Nai-Chung N Chang, Ming Yin, Jeffrey W Shevach, Weiyan Li, Tyler J Nelson, Anthony Gao, Kathryn M Pridgen, Martin W Schoen, Scott L DuVall, Yu-Ning Wong, Julie A Lynch, Patrick R Alba","doi":"10.1200/CCI-24-00189","DOIUrl":"10.1200/CCI-24-00189","url":null,"abstract":"<p><strong>Purpose: </strong>This study introduces an integrated approach using structured and unstructured data from an electronic health record to identify and characterize patient utilization of hereditary cancer genetic testing among patients with metastatic castration-resistant prostate cancer (mCRPC). Secondary objectives were to describe factors associated with the receipt of testing.</p><p><strong>Methods: </strong>This retrospective cohort study included a cohort of Veterans diagnosed with mCRPC from January 2016 to December 2021. Receipt of genetic testing was identified using structured and unstructured data. Time to testing, age at testing, and testing rate were analyzed. Sociodemographic and clinical factors associated with receipt of hereditary cancer genetic testing were identified including race, marital status, rurality, Charlson comorbidity index (CCI), and genetic counseling.</p><p><strong>Results: </strong>Among 9,703 Veterans with mCRPC who did not decline testing, 16% received genetic testing, with nearly half of the tests occurring in 2020-2021. Factors positively associated with genetic testing included receipt of genetic counseling (adjusted odds ratio [aOR], 11.07 [95% CI, 3.66 to 33.51]), enrollment in clinical trial (aOR, 7.42 [95% CI, 5.59 to 9.84]), and treatment at a Prostate Cancer Foundation-Veterans Affairs Center of Excellence (aOR, 1.43 [95% CI, 1.04 to 1.95]). Negative associations included older age (aOR, 0.95 [95% CI, 0.93 to 0.97]) and severe CCI score (aOR, 0.82 [95% CI, 0.71 to 0.94]). Trends revealed that time to testing decreased per diagnosis year while median age at testing increased per year.</p><p><strong>Conclusion: </strong>Although testing rates are still suboptimal, they have increased steadily since 2016. Educating Veterans about the benefits of genetic testing may further improve testing rates.</p>","PeriodicalId":51626,"journal":{"name":"JCO Clinical Cancer Informatics","volume":"9 ","pages":"e2400189"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11834961/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143392532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancements in Interoperability: Achieving Anatomic Pathology Reports That Adhere to International Standards and Are Both Human-Readable and Readily Computable.","authors":"Walter S Campbell, Brian A Rous, Stefan Dubois, Paul A Seegers, Rajesh C Dash, Thomas Rüdiger, Suzanne Santamaria, Elaine Wooler, James Case, Lazslo Igali, Mary E Edgerton, Ross W Simpson, Ekaterina Bazyleva, George Birdsong, Richard Moldwin, Timothy R Helliwell, Peter Paul Yu, John Srigley","doi":"10.1200/CCI-24-00180","DOIUrl":"https://doi.org/10.1200/CCI-24-00180","url":null,"abstract":"<p><strong>Purpose: </strong>Over the past 50 years, multiple pathology organizations worldwide have evolved in cancer histopathology reporting from subjective, narrative assessments to structured, synoptic formats using controlled vocabulary. These reporting protocols include the required data elements that represent the minimum set of evidence-based, clinically actionable parameters necessary to convey the diagnostic, prognostic, and predictive information essential for patient care. Despite these advances, the synoptic reporting protocols were not harmonized across the various pathology organizations. Cancer pathology continues to be widely reported and stored in free-text format, or without encoded data such that it is neither computable nor interoperable across organizations.</p><p><strong>Methods: </strong>In 2020, SNOMED International created the Cancer Synoptic Reporting Working Group (CSRWG). This resulted in international collaboration across multiple pathology organizations. CCRWG's mission was to use SNOMED Clinical Terms (CT) concepts to represent the required content within the College of American Pathologists (CAP) and International Collaboration on Cancer Reporting (ICCR) published pathology reporting protocols.</p><p><strong>Results: </strong>In late 2023, the CSRWG published over 1,300 new or revised SNOMED CT concepts to represent all required pathology cancer data elements for adult and pediatric solid tumors in both CAP and ICCR using the semantic principles of the SNOMED-CT concept model. Thus, computability and interoperability would be broadly established.</p><p><strong>Conclusion: </strong>This work brings to fruition the longstanding desire for an international, interoperable, human- and machine-readable cancer pathology report for use in patient care, health care quality improvement, population health, public health surveillance, and translational and clinical trial research. The following report describes the project, its methods, and applications in the stated use cases.</p>","PeriodicalId":51626,"journal":{"name":"JCO Clinical Cancer Informatics","volume":"9 ","pages":"e2400180"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143257239","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}

{"title":"Erratum: Measurement of Completeness and Timeliness of Linked Electronic Health Record Pharmacy Data for Early Detection of Nonadherence to Breast Cancer Adjuvant Endocrine Therapy.","authors":"Chelsea McPeek, Shirlene Paul, Jordan Lieberenz, Mia Levy","doi":"10.1200/CCI-25-00009","DOIUrl":"https://doi.org/10.1200/CCI-25-00009","url":null,"abstract":"","PeriodicalId":51626,"journal":{"name":"JCO Clinical Cancer Informatics","volume":"9 ","pages":"e2500009"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143442956","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}