Michelle C. Feng

888 total citations · 1 hit paper
5 papers, 578 citations indexed

About

Michelle C. Feng is a scholar working on General Health Professions, Cognitive Neuroscience and Experimental and Cognitive Psychology. According to data from OpenAlex, Michelle C. Feng has authored 5 papers receiving a total of 578 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in General Health Professions, 2 papers in Cognitive Neuroscience and 2 papers in Experimental and Cognitive Psychology. Recurrent topics in Michelle C. Feng's work include Geriatric Care and Nursing Homes (2 papers), Creativity in Education and Neuroscience (1 paper) and Dementia and Cognitive Impairment Research (1 paper). Michelle C. Feng is often cited by papers focused on Geriatric Care and Nursing Homes (2 papers), Creativity in Education and Neuroscience (1 paper) and Dementia and Cognitive Impairment Research (1 paper). Michelle C. Feng collaborates with scholars based in United States. Michelle C. Feng's co-authors include Michelle E. Mlinac, Gerald C. Davison, Michael E. Dawson, Mara Mather, Kean J. Hsu, Kalina N. Babeva, Christopher G. Courtney, Justin F. Hummer, Margaret Murphy and Nikolaos Malandrakis and has published in prestigious journals such as Frontiers in Psychology, Psychology and Aging and Archives of Clinical Neuropsychology.

In The Last Decade

Michelle C. Feng

5 papers receiving 563 citations

Hit Papers

align trajectories

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.

Assessment of Activities of Daily Living, Self-Care, and Independence

2016 531 citations Michelle E. Mlinac, Michelle C. Feng Archives of Clinical Neuropsychology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michelle C. Feng United States	5	168	120	74	67	66	5	578
Michelle E. Mlinac United States	5	174 1.0×	135 1.1×	73 1.0×	68 1.0×	68 1.0×	10	578
Linda Beuscher United States	16	168 1.0×	194 1.6×	67 0.9×	61 0.9×	64 1.0×	24	676
Karin M. Volkers Netherlands	11	207 1.2×	110 0.9×	47 0.6×	69 1.0×	124 1.9×	30	551
Takayuki Tabira Japan	14	142 0.8×	102 0.8×	79 1.1×	85 1.3×	123 1.9×	66	599
Catarina Pereira Portugal	16	147 0.9×	75 0.6×	50 0.7×	63 0.9×	145 2.2×	50	572
Pamela Toto United States	10	285 1.7×	161 1.3×	53 0.7×	121 1.8×	55 0.8×	28	830
Minmin Leng China	13	254 1.5×	155 1.3×	48 0.6×	46 0.7×	70 1.1×	25	709
Hui Feng China	16	297 1.8×	145 1.2×	83 1.1×	72 1.1×	174 2.6×	75	841
Emylucy Martins Paiva Paradela Brazil	8	240 1.4×	129 1.1×	82 1.1×	29 0.4×	66 1.0×	13	545
Emily J. Henderson United Kingdom	17	247 1.5×	135 1.1×	34 0.5×	43 0.6×	87 1.3×	73	1.2k

Countries citing papers authored by Michelle C. Feng

Since Specialization

Citations

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

Fields of papers citing papers by Michelle C. Feng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michelle C. Feng. 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 Michelle C. Feng. The network helps show where Michelle C. Feng may publish in the future.

Co-authorship network of co-authors of Michelle C. Feng

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

All Works

Sort: Min cites: Since: Top N: Style:

5 of 5 papers shown

1.

Mlinac, Michelle E. & Michelle C. Feng. (2016). Assessment of Activities of Daily Living, Self-Care, and Independence. Archives of Clinical Neuropsychology. 31(6). 506–516. 531 indexed citations breakdown →

2.

Feng, Michelle C., Margaret Murphy, & Michelle E. Mlinac. (2016). Independent Living Capacity Evaluation in Home-Based Primary Care: Considerations and Outcomes of a Quality Improvement Project. Clinical Gerontologist. 40(1). 51–62. 5 indexed citations

3.

Hsu, Kean J., Kalina N. Babeva, Michelle C. Feng, Justin F. Hummer, & Gerald C. Davison. (2014). Experimentally induced distraction impacts cognitive but not emotional processes in think-aloud cognitive assessment. Frontiers in Psychology. 5. 474–474. 15 indexed citations

4.

Malandrakis, Nikolaos, Alexandros Potamianos, Kean J. Hsu, et al.. (2014). Affective language model adaptation via corpus selection. 4. 4838–4842. 6 indexed citations

5.

Feng, Michelle C., Christopher G. Courtney, Mara Mather, Michael E. Dawson, & Gerald C. Davison. (2011). Age-related affective modulation of the startle eyeblink response: Older adults startle most when viewing positive pictures.. Psychology and Aging. 26(3). 752–760. 21 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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