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  1. 2021
    “…Longitudinal cellular immune reconstitution data were analyzed conventionally and with a data science approach using clustering with dynamic time warping to determine the similarity between time-series of T cell subsets. …”
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    Time series clustering of T cell subsets dissects heterogeneity in immune reconstitution and clinical outcomes among MUD-HCT patients receiving ATG or PTCy
  2. 2022
    “…A retrospective medical record review was performed for all patients in the database of the Health and Welfare Data Science Center covered by National Health Insurance in Taiwan from January 2010 until December 2019. …”
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    Prevalence and Comorbidity of Gender Dysphoria in Taiwan, 2010–2019
  3. 2023
    “…METHODS/STUDY POPULATION: This is a retrospective, big data science study. Data from Veterans Affairs (VA) medical centers across the United States between the start of 2020 and the end of 2022 were utilized. …”
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    58 Utilizing VA Data to Define Long COVID and Identify Patients at Risk
  4. 2024
    “…Based on this data, we investigate the possibility of forecasting heat demand using a variety of time series models and offline and online machine learning (ML) techniques in a standard data science approach. We chose to analyze different modeling techniques as they can be used in different settings, where time series models require no additional data, offline ML needs a lot of data gathered up front, and online ML could be deployed from day one. …”
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    Forecasting of residential unit’s heat demands: a comparison of machine learning techniques in a real-world case study
  5. 2025
    por Ahalt, Stan, Avillach, Paul, Boyles, Rebecca, Bradford, Kira, Cox, Steven, Davis-Dusenbery, Brandi, Grossman, Robert L, Krishnamurthy, Ashok, Manning, Alisa, Paten, Benedict, Philippakis, Anthony, Borecki, Ingrid, Chen, Shu Hui, Kaltman, Jon, Ladwa, Sweta, Schwartz, Chip, Thomson, Alastair, Davis, Sarah, Leaf, Alison, Lyons, Jessica, Sheets, Elizabeth, Bis, Joshua C, Conomos, Matthew, Culotti, Alessandro, Desain, Thomas, Digiovanna, Jack, Domazet, Milan, Gogarten, Stephanie, Gutierrez-Sacristan, Alba, Harris, Tim, Heavner, Ben, Jain, Deepti, O'Connor, Brian, Osborn, Kevin, Pillion, Danielle, Pleiness, Jacob, Rice, Ken, Rupp, Garrett, Serret-Larmande, Arnaud, Smith, Albert, Stedman, Jason P, Stilp, Adrienne, Barsanti, Teresa, Cheadle, John, Erdmann, Christopher, Farlow, Brandy, Gartland-Gray, Allie, Hayes, Julie, Hiles, Hannah, Kerr, Paul, Lenhardt, Chris, Madden, Tom, Mieczkowska, Joanna O, Miller, Amanda, Patton, Patrick, Rathbun, Marcie, Suber, Stephanie, Asare, Joe
    Publicado 2023
    “…This ecosystem provides secure, cloud-based workspaces, user authentication and authorization, search, tools and workflows, applications, and new innovative features to address community needs, including exploratory data analysis, genomic and imaging tools, tools for reproducibility, and improved interoperability with other NIH data science platforms. BDC offers straightforward access to large-scale datasets and computational resources that support precision medicine for heart, lung, blood, and sleep conditions, leveraging separately developed and managed platforms to maximize flexibility based on researcher needs, expertise, and backgrounds. …”
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    Building a collaborative cloud platform to accelerate heart, lung, blood, and sleep research
  6. 2026
    “…PURPOSE: Recent advances in Surgical Data Science (SDS) have contributed to an increase in video recordings from hospital environments. …”
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    DisguisOR: holistic face anonymization for the operating room
  7. 2027
    “…OBJECTIVES: Two interlinked surveys were organised by the British Heart Foundation Data Science Centre, which aimed to establish national priorities for cardiovascular imaging research. …”
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    Cardiovascular imaging research priorities
  8. 2028
    “…Upon immunohistochemical (IHC) analysis of FFPE blocks however, COL1A2 showed better differential staining between tumor epithelia and tumor stroma. Similar data science driven approach utilizing single cell sequencing and RNAseq data from stabilized CAFs can be employed to identify CAF-markers in various cancers.…”
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    Novel CAF-identifiers via transcriptomic and protein level analysis in HNSC patients
  9. 2029
    por Li, Shengwen Calvin
    Publicado 2023
    “…Reflecting on retrospective data science, it is evident that well-cited articles can wield a transformative influence on the Journal Citation Reports Impact Factor score, as exemplified by Robert Weinberg’s landmark on cancer (Hanahan and Weinberg, 2011). …”
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    Mastering the craft: Creating an insightful and widely-cited literature review
  10. 2030
    “…METHODS: In order to efficiently leverage the wealth of information, we here assessed several genomic data science tools. The rationale to focus on on-premise installations is to cope with situations where data confidentiality and compliance regulations etc. rule out cloud based solutions. …”
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    Critical assessment of on-premise approaches to scalable genome analysis
  11. 2031
    “…APPROACH: The study will deploy a mobile application (app) platform and use novel data science analytic approaches (Artificial Intelligence and Machine Learning) to identifying predictors of mental health disorders among 500 randomly sampled healthcare workers from five healthcare facilities in Nairobi, Kenya. …”
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    Use of mobile technology to identify behavioral mechanisms linked to mental health outcomes in Kenya: protocol for development and validation of a predictive model
  12. 2032
    “…We infused clinical information with engineering systems modeling and data science to develop a time-by-utilization profile per patient group at each hospital using US Medicare hospice utilization data for a cohort of patients with advanced (poor-prognosis) cancer that died April-December 2016. …”
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    Clinically informed machine learning elucidates the shape of hospice racial disparities within hospitals
  13. 2033
    “…Therefore, gene selection, also known as feature selection in data science, plays an important role in selecting informative genes for scRNA-seq cell type identification. …”
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    On the use of QDE-SVM for gene feature selection and cell type classification from scRNA-seq data
  14. 2034
    “…Finally, these goals can be more rapidly achieved with data science efforts, data harmonisation between studies and with sustainable data‐sharing practices. …”
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    Strengthening the evidence to improve health outcomes of children with perinatal HIV exposure
  15. 2035
    “…In this study, the important affecting parameters on the anode side of catalyst in PEMWE and analyzed them by machine-learning (ML) algorithms through developing a data science (DS) procedure were discussed. Various machine learning models were subjected to comparison, wherein the Decision Tree models, specifically those configured with maximum depths of 3 and 4, emerged as the optimal choices, attaining a perfect 100% accuracy across both Dataset 1 and Dataset 2. …”
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    Evaluating algorithms of decision tree, support vector machine and regression for anode side catalyst data in proton exchange membrane water electrolysis
  16. 2036
    “…FINDINGS: We therefore set up a telemetry-based system (Data Science International, DSI™) that continuously monitored the rat's temperature, heart rate and activity in their cages. …”
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    A mobile phone based alarm system for supervising vital parameters in free moving rats
  17. 2037
    “…Conclusions: Using an inductive data science approach, the gradient boosting model identified predictors consistent with previous experimental work in aggression; specifically psychopathy and trauma exposure. …”
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    Genetic and Psychosocial Predictors of Aggression: Variable Selection and Model Building With Component-Wise Gradient Boosting
  18. 2038
    “…BACKGROUND: ILÚM Heath Solutions, an infectious diseases software platform, developed precision antibiotic therapy (PAT) software to guide selection of therapy using data science, patient-specific factors, as well as historical patient, pharmacy, and microbiologic data. …”
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    1814. External Validation of Precision Antibiotic Therapy for Enterococcal Bloodstream Infections
  19. 2039
    “…CONCLUSIONS: We suggest that data science approaches can be used effectively in the clinical domain in a way that does not disrupt preexisting expert classification and that enhances the utility of existing coding systems. …”
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    A nomenclature and classification for the congenital myasthenic syndromes: preparing for FAIR data in the genomic era
  20. 2040
    por Miller, D. Douglas
    Publicado 2019
    “…Efficient and accurate AI analytics require fastidious data science—the careful curating of knowledge representations in databases, decomposition of data matrices to reduce dimensionality, and preprocessing of datasets to mitigate the confounding effects of messy (i.e., missing, redundant, and outlier) data. …”
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    The medical AI insurgency: what physicians must know about data to practice with intelligent machines
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