Milena Gianfrancesco

7.2k total citations · 1 hit paper
51 papers, 2.6k citations indexed

About

Milena Gianfrancesco is a scholar working on Rheumatology, Pathology and Forensic Medicine and Immunology. According to data from OpenAlex, Milena Gianfrancesco has authored 51 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Rheumatology, 17 papers in Pathology and Forensic Medicine and 9 papers in Immunology. Recurrent topics in Milena Gianfrancesco's work include Systemic Lupus Erythematosus Research (15 papers), Rheumatoid Arthritis Research and Therapies (13 papers) and Multiple Sclerosis Research Studies (7 papers). Milena Gianfrancesco is often cited by papers focused on Systemic Lupus Erythematosus Research (15 papers), Rheumatoid Arthritis Research and Therapies (13 papers) and Multiple Sclerosis Research Studies (7 papers). Milena Gianfrancesco collaborates with scholars based in United States, Sweden and Australia. Milena Gianfrancesco's co-authors include Jinoos Yazdany, Gabriela Schmajuk, Suzanne Tamang, Lisa F. Barcellos, Lars Alfredsson, Tomas Olsson, Anna Karin Hedström, Catherine Schaefer, Neal D. Goldstein and Atul J. Butte and has published in prestigious journals such as Nature Medicine, Nature Communications and Neurology.

In The Last Decade

Milena Gianfrancesco

50 papers receiving 2.6k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Potential Biases in Machine Learning Algorithms Using Electronic Health Record Data

2018 771 citations Milena Gianfrancesco, Suzanne Tamang et al. JAMA Internal Medicine profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Milena Gianfrancesco United States	21	546	530	479	413	312	51	2.6k
Gabriela Schmajuk United States	30	314 0.6×	384 0.7×	386 0.8×	1.5k 3.5×	291 0.9×	126	3.3k
Wei‐Qi Wei United States	25	188 0.3×	393 0.7×	680 1.4×	152 0.4×	301 1.0×	100	4.1k
Vivian S. Gainer United States	40	316 0.6×	109 0.2×	1.0k 2.2×	433 1.0×	192 0.6×	95	4.7k
Katherine P. Liao United States	41	547 1.0×	84 0.2×	696 1.5×	1.8k 4.5×	330 1.1×	164	5.2k
Omid Khalilzadeh Iran	32	275 0.5×	186 0.4×	149 0.3×	128 0.3×	829 2.7×	93	4.2k
Euijung Ryu United States	34	116 0.2×	104 0.2×	189 0.4×	80 0.2×	412 1.3×	129	2.8k
Lisa C. Adams Germany	26	51 0.1×	427 0.8×	306 0.6×	136 0.3×	735 2.4×	133	2.1k
Linn Abraham United States	27	424 0.8×	83 0.2×	1.3k 2.6×	266 0.6×	1.1k 3.4×	57	4.1k
Tej D. Azad United States	30	812 1.5×	81 0.2×	65 0.1×	82 0.2×	352 1.1×	161	4.8k
Shahrukh K. Hashmi United States	30	156 0.3×	64 0.1×	144 0.3×	69 0.2×	263 0.8×	195	3.6k

Countries citing papers authored by Milena Gianfrancesco

Since Specialization

Citations

This map shows the geographic impact of Milena Gianfrancesco'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 Milena Gianfrancesco with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Milena Gianfrancesco more than expected).

Fields of papers citing papers by Milena Gianfrancesco

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Milena Gianfrancesco. 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 Milena Gianfrancesco. The network helps show where Milena Gianfrancesco may publish in the future.

Co-authorship network of co-authors of Milena Gianfrancesco

This figure shows the co-authorship network connecting the top 25 collaborators of Milena Gianfrancesco. A scholar is included among the top collaborators of Milena Gianfrancesco 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 Milena Gianfrancesco. Milena Gianfrancesco is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Gianfrancesco, Milena, et al.. (2025). On the use of natural language processing to implement the target trial framework using unstructured data from the electronic health record. PubMed. 9. 100204–100204.

Izadi, Zara, et al.. (2024). Development and validation of a risk scoring system to identify patients with lupus nephritis in electronic health record data. Lupus Science & Medicine. 11(1). e001170–e001170. 2 indexed citations

Tamang, Suzanne, et al.. (2022). Practical Considerations for Developing Clinical Natural Language Processing Systems for Population Health Management and Measurement. JMIR Medical Informatics. 11. e37805–e37805. 13 indexed citations

Gianfrancesco, Milena, Maria Dall’Era, Louise B. Murphy, et al.. (2021). Mortality Among Minority Populations with Systemic Lupus Erythematosus, Including Asian and Hispanic/Latino Persons — California, 2007–2017. MMWR Morbidity and Mortality Weekly Report. 70(7). 236–239. 23 indexed citations

Gianfrancesco, Milena, Zara Izadi, Claire Harrison, et al.. (2020). Race/ethnicity Is Associated with Poor Health Outcomes Amongst Rheumatic Disease Patients Diagnosed with COVID-19 in the US: Data from the COVID-19 Global Rheumatology Alliance Physician-Reported Registry. Arthritis & Rheumatism. 72. 3–3. 1 indexed citations

Gianfrancesco, Milena, Charles E. McCulloch, Laura Trupin, et al.. (2020). Reweighting to address nonparticipation and missing data bias in a longitudinal electronic health record study. Annals of Epidemiology. 50. 48–51.e2. 3 indexed citations

Gianfrancesco, Milena, Kimme L Hyrich, Laure Gossec, et al.. (2020). Rheumatic disease and COVID-19: initial data from the COVID-19 Global Rheumatology Alliance provider registries. The Lancet Rheumatology. 2(5). e250–e253. 133 indexed citations

Gianfrancesco, Milena, Jinoos Yazdany, & Philip C. Robinson. (2020). Epidemiology and outcomes of novel coronavirus 2019 in patients with immune-mediated inflammatory diseases. Current Opinion in Rheumatology. 32(5). 434–440. 42 indexed citations

Gianfrancesco, Milena, et al.. (2019). Increased Risk of Ischemic Stroke in Systemic Sclerosis: A National Cohort Study of US Veterans. The Journal of Rheumatology. 47(1). 82–88. 14 indexed citations

10.

Lanata, Cristina, Ishan Paranjpe, Joanne Nititham, et al.. (2019). A phenotypic and genomics approach in a multi-ethnic cohort to subtype systemic lupus erythematosus. Nature Communications. 10(1). 3902–3902. 38 indexed citations

11.

Li, Jing, Jinoos Yazdany, Laura Trupin, et al.. (2018). Capturing a Patient-Reported Measure of Physical Function Through an Online Electronic Health Record Patient Portal in an Ambulatory Clinic: Implementation Study. JMIR Medical Informatics. 6(2). e31–e31. 10 indexed citations

12.

Gianfrancesco, Milena, Laura Trupin, Stephen Shiboski, et al.. (2018). Smoking Is Associated with Higher Disease Activity in Rheumatoid Arthritis: A Longitudinal Study Controlling for Time-varying Covariates. The Journal of Rheumatology. 46(4). 370–375. 27 indexed citations

13.

Gianfrancesco, Milena, Suzanne Tamang, Jinoos Yazdany, & Gabriela Schmajuk. (2018). Potential Biases in Machine Learning Algorithms Using Electronic Health Record Data. JAMA Internal Medicine. 178(11). 1544–1544. 771 indexed citations breakdown →

14.

Mowry, Ellen M., Anna Karin Hedström, Milena Gianfrancesco, et al.. (2018). Incorporating machine learning approaches to assess putative environmental risk factors for multiple sclerosis. Multiple Sclerosis and Related Disorders. 24. 135–141. 12 indexed citations

15.

Hedström, Anna Karin, Michail Katsoulis, Ola Hössjer, et al.. (2017). The interaction between smoking and HLA genes in multiple sclerosis: replication and refinement. European Journal of Epidemiology. 32(10). 909–919. 40 indexed citations

16.

Jafri, Kashif, Alexis Ogdie, Atif Qasim, et al.. (2017). Discordance of the Framingham cardiovascular risk score and the 2013 American College of Cardiology/American Heart Association risk score in systemic lupus erythematosus and rheumatoid arthritis. Clinical Rheumatology. 37(2). 467–474. 18 indexed citations

17.

Gianfrancesco, Milena & Lisa F. Barcellos. (2016). Obesity and Multiple Sclerosis Susceptibility: A Review. PubMed. 1(7). 1–5. 79 indexed citations

18.

Hedström, Anna Karin, Ellen M. Mowry, Milena Gianfrancesco, et al.. (2016). High consumption of coffee is associated with decreased multiple sclerosis risk; results from two independent studies. Journal of Neurology Neurosurgery & Psychiatry. 87(5). 454–460. 65 indexed citations

19.

Mowry, Ellen M., Anna Karin Hedström, Milena Gianfrancesco, et al.. (2015). Greater Consumption of Coffee is Associated with Reduced Odds of Multiple Sclerosis (S45.004). Neurology. 84(14_supplement). 2 indexed citations

20.

Lo, Albert, et al.. (2010). Reduction of freezing of gait in Parkinson's disease by repetitive robot-assisted treadmill training: a pilot study. Journal of NeuroEngineering and Rehabilitation. 7(1). 51–51. 72 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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