Daniel M. Libby

7.5k total citations · 1 hit paper
48 papers, 5.3k citations indexed

About

Daniel M. Libby is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Surgery. According to data from OpenAlex, Daniel M. Libby has authored 48 papers receiving a total of 5.3k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Pulmonary and Respiratory Medicine, 19 papers in Radiology, Nuclear Medicine and Imaging and 7 papers in Surgery. Recurrent topics in Daniel M. Libby's work include Lung Cancer Diagnosis and Treatment (22 papers), Lung Cancer Treatments and Mutations (14 papers) and Radiomics and Machine Learning in Medical Imaging (14 papers). Daniel M. Libby is often cited by papers focused on Lung Cancer Diagnosis and Treatment (22 papers), Lung Cancer Treatments and Mutations (14 papers) and Radiomics and Machine Learning in Medical Imaging (14 papers). Daniel M. Libby collaborates with scholars based in United States, Canada and Spain. Daniel M. Libby's co-authors include Claudia I. Henschke, James P. Smith, Mark Pasmantier, David F. Yankelevitz, Nasser K. Altorki, Dorothy I. McCauley, Olli S. Miettinen, David P. Naidich, Georgeann McGuinness and June H. Koizumi and has published in prestigious journals such as New England Journal of Medicine, The Lancet and JAMA.

In The Last Decade

Daniel M. Libby

48 papers receiving 5.1k citations

Hit Papers

Early Lung Cancer Action ... 1999 2026 2008 2017 1999 500 1000 1.5k

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Daniel M. Libby 3.7k 2.1k 771 423 410 48 5.3k
Michael A. Maddaus 3.8k 1.0× 553 0.3× 1.4k 1.8× 328 0.8× 1.8k 4.4× 130 6.0k
Johny Verschakelen 4.2k 1.2× 1.6k 0.8× 478 0.6× 1.0k 2.4× 1.0k 2.6× 190 6.2k
Dima Abi-Said 1.1k 0.3× 968 0.5× 532 0.7× 1.4k 3.3× 852 2.1× 35 4.7k
Alain Borczuk 4.3k 1.2× 628 0.3× 2.2k 2.9× 632 1.5× 888 2.2× 181 8.6k
Claus Peter Heußel 4.7k 1.3× 2.0k 1.0× 1.7k 2.2× 1.8k 4.2× 654 1.6× 336 8.4k
S Stanzel 692 0.2× 1.3k 0.6× 488 0.6× 286 0.7× 353 0.9× 93 3.5k
Carl R. Fuhrman 1.6k 0.4× 930 0.5× 282 0.4× 1.2k 2.8× 701 1.7× 91 3.9k
Birgit Weynand 1.8k 0.5× 712 0.3× 1.6k 2.0× 515 1.2× 1.0k 2.5× 188 5.0k
Brendon M. Stiles 3.6k 1.0× 508 0.2× 1.9k 2.4× 390 0.9× 1.6k 4.0× 175 6.3k
Elizabeth C. Jones 1.5k 0.4× 1.1k 0.5× 1.4k 1.8× 486 1.1× 483 1.2× 112 5.7k

Countries citing papers authored by Daniel M. Libby

Since Specialization
Citations

This map shows the geographic impact of Daniel M. Libby's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel M. Libby with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel M. Libby more than expected).

Fields of papers citing papers by Daniel M. Libby

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel M. Libby. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel M. Libby. The network helps show where Daniel M. Libby may publish in the future.

Co-authorship network of co-authors of Daniel M. Libby

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel M. Libby. A scholar is included among the top collaborators of Daniel M. Libby based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel M. Libby. Daniel M. Libby is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Narula, Navneet, et al.. (2016). Imatinib Treatment of Lymphangiomatosis (Generalized Lymphatic Anomaly). Journal of the National Comprehensive Cancer Network. 14(4). 383–386. 6 indexed citations
2.
Altorki, Nasser K., et al.. (2014). Surgical Lung Biopsy in Adult Respiratory Distress Syndrome: A Meta-Analysis. The Annals of Thoracic Surgery. 98(4). 1254–1260. 36 indexed citations
3.
Kim, Won Bae, Daniel M. Libby, James P. Smith, et al.. (2012). Radiographic and Clinical Characterization of False Negative Results from CT-Guided Needle Biopsies of Lung Nodules. Journal of Thoracic Oncology. 7(5). 815–820. 43 indexed citations
4.
Henschke, Claudia I., David F. Yankelevitz, Rowena Yip, et al.. (2012). Lung Cancers Diagnosed at Annual CT Screening: Volume Doubling Times. Radiology. 263(2). 578–583. 159 indexed citations
5.
Gallagher, David, Daniel M. Libby, & Nancy E. Kemeny. (2009). Elevated Carcinoembryonic Antigen and Sarcoidosis Masquerading as Metastatic Colon Cancer. Clinical Colorectal Cancer. 8(3). 172–174. 3 indexed citations
6.
Libby, Daniel M., Ning Wu, Injae Lee, et al.. (2006). CT Screening for Lung Cancer. CHEST Journal. 129(4). 1039–1042. 48 indexed citations
7.
Libby, Daniel M., James P. Smith, Nasser K. Altorki, et al.. (2004). Managing the Small Pulmonary Nodule Discovered by CT. CHEST Journal. 125(4). 1522–1529. 155 indexed citations
8.
Henschke, Claudia I., David F. Yankelevitz, David P. Naidich, et al.. (2004). CT Screening for Lung Cancer: Suspiciousness of Nodules according to Size on Baseline Scans. Radiology. 231(1). 164–168. 261 indexed citations
9.
Port, Jeffrey L., Michael S. Kent, Robert J. Korst, et al.. (2003). Tumor Size Predicts Survival Within Stage IA Non-Small Cell Lung Cancer *. CHEST Journal. 124(5). 1828–1833. 130 indexed citations
10.
Henschke, Claudia I., David F. Yankelevitz, Dorothy I. McCauley, et al.. (2003). Guidelines for the use of spiral computed tomography in screening for lung cancer. European Respiratory Journal. 21(39 suppl). 45s–51s. 16 indexed citations
11.
Henschke, Claudia I., David F. Yankelevitz, Daniel M. Libby, et al.. (2002). Computed tomography screening for lung cancer. Clinics in Chest Medicine. 23(1). 49–57. 5 indexed citations
12.
Henschke, Claudia I., David P. Naidich, David F. Yankelevitz, et al.. (2001). Early Lung Cancer Action Project. Cancer. 92(1). 153–159. 363 indexed citations
13.
Henschke, Claudia I., Dorothy I. McCauley, David F. Yankelevitz, et al.. (1999). Early Lung Cancer Action Project: overall design and findings from baseline screening. The Lancet. 354(9173). 99–105. 1871 indexed citations breakdown →
14.
Libby, Daniel M. & Dorothy A. White. (1998). PULMONARY TOXICITY OF DRUGS USED TO TREAT SYSTEMIC AUTOIMMUNE DISEASES. Clinics in Chest Medicine. 19(4). 809–821. 14 indexed citations
15.
Libby, Daniel M., et al.. (1997). Clinical utility of computed tomography in the diagnosis of pulmonary embolism. Clinical Imaging. 21(3). 175–182. 14 indexed citations
16.
Libby, Daniel M., Claudia I. Henschke, & David F. Yankelevitz. (1995). The solitary pulmonary nodule: Update 1995. The American Journal of Medicine. 99(5). 491–496. 37 indexed citations
17.
Henschke, Claudia I., Olli S. Miettinen, David F. Yankelevitz, Daniel M. Libby, & James P. Smith. (1994). Radiographic screening for cancer proposed paradigm for requisite research. Clinical Imaging. 18(1). 16–20. 55 indexed citations
18.
Jacobs, Jonathan L., Daniel M. Libby, David Gelmont, et al.. (1991). A Cluster ofPneumocystis cariniiPneumonia in Adults without Predisposing Illnesses. New England Journal of Medicine. 324(4). 246–250. 100 indexed citations
19.
Libby, Daniel M., Nasser K. Altorki, Jeffrey P. Gold, et al.. (1990). Simultaneous Pulmonary and Renal Malignancy. CHEST Journal. 98(1). 153–156. 9 indexed citations
20.
Libby, Daniel M., et al.. (1988). IFN-gamma-activated human alveolar macrophages inhibit the intracellular multiplication of Legionella pneumophila .. The Journal of Immunology. 140(11). 3978–3981. 96 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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