Browsing by Author "Del Fiol, Guilherme"

Now showing 1 - 3 of 3
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    A New Era of Data-Driven Cancer Research and Care: Opportunities and Challenges
    (American Association for Cancer Research, 2024) Gomez, Felicia; Danos, Arpad M.; Del Fiol, Guilherme; Madabhushi, Anant; Tiwari, Pallavi; McMichael, Joshua F.; Bakas, Spyridon; Bian, Jiang; Davatzikos, Christos; Fertig, Elana J.; Kalpathy-Cramer, Jayashree; Kenney, Johanna; Savova, Guergana K.; Yetisgen, Meliha; Van Allen, Eliezer M.; Warner, Jeremy L.; Prior, Fred; Griffith, Malachi; Griffith, Obi L.; Pathology and Laboratory Medicine, School of Medicine
    People diagnosed with cancer and their formal and informal caregivers are increasingly faced with a deluge of complex information, thanks to rapid advancements in the type and volume of diagnostic, prognostic, and treatment data. This commentary discusses the opportunities and challenges that the society faces as we integrate large volumes of data into regular cancer care.
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    A research agenda to support the development and implementation of genomics-based clinical informatics tools and resources
    (Oxford University Press, 2022) Wiley, Ken; Findley, Laura; Goldrich, Madison; Rakhra-Burris, Tejinder K.; Stevens, Ana; Williams, Pamela; Bult, Carol J.; Chisholm, Rex; Deverka, Patricia; Ginsburg, Geoffrey S.; Green, Eric D.; Jarvik, Gail; Mensah, George A.; Ramos, Erin; Relling, Mary V.; Roden, Dan M.; Rowley, Robb; Alterovitz, Gil; Aronson, Samuel; Bastarache, Lisa; Cimino, James J.; Crowgey, Erin L.; Del Fiol, Guilherme; Freimuth, Robert R.; Hoffman, Mark A.; Jeff, Janina; Johnson, Kevin; Kawamoto, Kensaku; Madhavan, Subha; Mendonca, Eneida A.; Ohno-Machado, Lucila; Pratap, Siddharth; Overby Taylor, Casey; Ritchie, Marylyn D.; Walton, Nephi; Weng, Chunhua; Zayas-Cabán, Teresa; Manolio, Teri A.; Williams, Marc S.; Pediatrics, School of Medicine
    Objective: The Genomic Medicine Working Group of the National Advisory Council for Human Genome Research virtually hosted its 13th genomic medicine meeting titled "Developing a Clinical Genomic Informatics Research Agenda". The meeting's goal was to articulate a research strategy to develop Genomics-based Clinical Informatics Tools and Resources (GCIT) to improve the detection, treatment, and reporting of genetic disorders in clinical settings. Materials and methods: Experts from government agencies, the private sector, and academia in genomic medicine and clinical informatics were invited to address the meeting's goals. Invitees were also asked to complete a survey to assess important considerations needed to develop a genomic-based clinical informatics research strategy. Results: Outcomes from the meeting included identifying short-term research needs, such as designing and implementing standards-based interfaces between laboratory information systems and electronic health records, as well as long-term projects, such as identifying and addressing barriers related to the establishment and implementation of genomic data exchange systems that, in turn, the research community could help address. Discussion: Discussions centered on identifying gaps and barriers that impede the use of GCIT in genomic medicine. Emergent themes from the meeting included developing an implementation science framework, defining a value proposition for all stakeholders, fostering engagement with patients and partners to develop applications under patient control, promoting the use of relevant clinical workflows in research, and lowering related barriers to regulatory processes. Another key theme was recognizing pervasive biases in data and information systems, algorithms, access, value, and knowledge repositories and identifying ways to resolve them.
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    Best practices to evaluate the impact of biomedical research software-metric collection beyond citations
    (Oxford University Press, 2024) Afiaz, Awan; Ivanov, Andrey A.; Chamberlin, John; Hanauer, David; Savonen, Candace L.; Goldman, Mary J.; Morgan, Martin; Reich, Michael; Getka, Alexander; Holmes, Aaron; Pati, Sarthak; Knight, Dan; Boutros, Paul C.; Bakas, Spyridon; Caporaso, J. Gregory; Del Fiol, Guilherme; Hochheiser, Harry; Haas, Brian; Schloss, Patrick D.; Eddy, James A.; Albrecht, Jake; Fedorov, Andrey; Waldron, Levi; Hoffman, Ava M.; Bradshaw, Richard L.; Leek, Jeffrey T.; Wright, Carrie; Pathology and Laboratory Medicine, School of Medicine
    Motivation: Software is vital for the advancement of biology and medicine. Impact evaluations of scientific software have primarily emphasized traditional citation metrics of associated papers, despite these metrics inadequately capturing the dynamic picture of impact and despite challenges with improper citation. Results: To understand how software developers evaluate their tools, we conducted a survey of participants in the Informatics Technology for Cancer Research (ITCR) program funded by the National Cancer Institute (NCI). We found that although developers realize the value of more extensive metric collection, they find a lack of funding and time hindering. We also investigated software among this community for how often infrastructure that supports more nontraditional metrics were implemented and how this impacted rates of papers describing usage of the software. We found that infrastructure such as social media presence, more in-depth documentation, the presence of software health metrics, and clear information on how to contact developers seemed to be associated with increased mention rates. Analysing more diverse metrics can enable developers to better understand user engagement, justify continued funding, identify novel use cases, pinpoint improvement areas, and ultimately amplify their software's impact. Challenges are associated, including distorted or misleading metrics, as well as ethical and security concerns. More attention to nuances involved in capturing impact across the spectrum of biomedical software is needed. For funders and developers, we outline guidance based on experience from our community. By considering how we evaluate software, we can empower developers to create tools that more effectively accelerate biological and medical research progress. Availability and implementation: More information about the analysis, as well as access to data and code is available at https://github.com/fhdsl/ITCR_Metrics_manuscript_website.