Mallory L. Hacker

628 total citations
28 papers, 383 citations indexed

About

Mallory L. Hacker is a scholar working on Neurology, Cellular and Molecular Neuroscience and Cognitive Neuroscience. According to data from OpenAlex, Mallory L. Hacker has authored 28 papers receiving a total of 383 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Neurology, 10 papers in Cellular and Molecular Neuroscience and 7 papers in Cognitive Neuroscience. Recurrent topics in Mallory L. Hacker's work include Neurological disorders and treatments (18 papers), Parkinson's Disease Mechanisms and Treatments (18 papers) and Botulinum Toxin and Related Neurological Disorders (7 papers). Mallory L. Hacker is often cited by papers focused on Neurological disorders and treatments (18 papers), Parkinson's Disease Mechanisms and Treatments (18 papers) and Botulinum Toxin and Related Neurological Disorders (7 papers). Mallory L. Hacker collaborates with scholars based in United States, Germany and United Kingdom. Mallory L. Hacker's co-authors include David Charles, Maxim Turchan, Thomas L. Davis, Lauren E. Heusinkveld, Peter E. Konrad, Amanda Currie, Fenna T. Phibbs, Peter Hedera, Anna Lia Molinari and Kevin R. Cannard and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and Neurology.

In The Last Decade

Mallory L. Hacker

25 papers receiving 372 citations

Peers

Mallory L. Hacker
Monique Giroux United States
Kelly Bertram Australia
Natlada Limotai United States
Christopher Tolleson United States
Jue Zhao China
Mallory L. Hacker
Citations per year, relative to Mallory L. Hacker Mallory L. Hacker (= 1×) peers Eavan McGovern

Countries citing papers authored by Mallory L. Hacker

Since Specialization
Citations

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

Fields of papers citing papers by Mallory L. Hacker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mallory L. Hacker. 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 Mallory L. Hacker. The network helps show where Mallory L. Hacker may publish in the future.

Co-authorship network of co-authors of Mallory L. Hacker

This figure shows the co-authorship network connecting the top 25 collaborators of Mallory L. Hacker. A scholar is included among the top collaborators of Mallory L. Hacker 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 Mallory L. Hacker. Mallory L. Hacker 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.
Hacker, Mallory L., Nanditha Rajamani, Thomas L. Davis, et al.. (2024). Evaluating a motor progression connectivity model across Parkinson’s disease stages. Journal of Neurology. 271(11). 7309–7315. 2 indexed citations
2.
Hacker, Mallory L., Michael G. Tramontana, Maxim Turchan, et al.. (2023). Long-term neuropsychological outcomes of deep brain stimulation in early-stage Parkinson's disease. Parkinsonism & Related Disorders. 113. 105479–105479. 3 indexed citations
3.
Hacker, Mallory L., Allison C. Waters, Jing Wang, et al.. (2023). Advances in Deep Brain Stimulation: From Mechanisms to Applications. Journal of Neuroscience. 43(45). 7575–7586. 12 indexed citations
4.
Hacker, Mallory L., Maxim Turchan, Kevin R. Cannard, et al.. (2022). Eleven-Year Outcomes of Deep Brain Stimulation in Early-Stage Parkinson Disease. Neuromodulation Technology at the Neural Interface. 26(2). 451–458. 10 indexed citations
5.
Bonnet, Kemberlee, et al.. (2022). Deep Brain Stimulation in Early-Stage Parkinson’s Disease: Patient Experience after 11 Years. Brain Sciences. 12(6). 766–766. 5 indexed citations
6.
Sortwell, Caryl E., Mallory L. Hacker, D. Luke Fischer, et al.. (2021). BDNF rs6265 Genotype Influences Outcomes of Pharmacotherapy and Subthalamic Nucleus Deep Brain Stimulation in Early-Stage Parkinson's Disease. Neuromodulation Technology at the Neural Interface. 25(6). 846–853. 8 indexed citations
7.
Hacker, Mallory L., Maxim Turchan, Thomas L. Davis, et al.. (2021). Early subthalamic nucleus deep brain stimulation in Parkinson’s disease reduces long-term medication costs. Clinical Neurology and Neurosurgery. 210. 106976–106976. 5 indexed citations
8.
Mitchell, Nia S., et al.. (2021). Exploring the presence of multiple abnormal non-motor features in patients with cervical dystonia. Journal of Clinical Neuroscience. 94. 315–320. 1 indexed citations
9.
Gill, Chandler E., Mallory L. Hacker, Maxim Turchan, et al.. (2020). Prevalence of Spasticity in Nursing Home Residents. Journal of the American Medical Directors Association. 21(8). 1157–1160. 7 indexed citations
10.
Simmons, Sandra F., et al.. (2020). The Minimum Data Set: An Opportunity to Improve Spasticity Screening. Journal of the American Medical Directors Association. 22(3). 608–612.
11.
Fischer, D. Luke, Peggy Auinger, John L. Goudreau, et al.. (2020). BDNF rs6265 Variant Alters Outcomes with Levodopa in Early-Stage Parkinson's Disease. Neurotherapeutics. 17(4). 1785–1795. 15 indexed citations
12.
Hacker, Mallory L., et al.. (2020). <p>A Simple Bedside Screening Tool for Spasticity Referral</p>. Clinical Interventions in Aging. Volume 15. 655–662. 4 indexed citations
13.
Harper, Kelly, et al.. (2020). A comparative evaluation of telehealth and direct assessment when screening for spasticity in residents of two long-term care facilities. Clinical Rehabilitation. 35(4). 589–594. 9 indexed citations
14.
Heusinkveld, Lauren E., Mallory L. Hacker, Maxim Turchan, Thomas L. Davis, & David Charles. (2018). Impact of Tremor on Patients With Early Stage Parkinson's Disease. Frontiers in Neurology. 9. 628–628. 31 indexed citations
15.
Hacker, Mallory L., Maxim Turchan, Amanda Currie, et al.. (2017). Subthalamic Nucleus Deep Brain Stimulation in Early Stage Parkinson’s Disease Reduces the Risk of Polypharmacy: Five-Year Analysis (P5.012). Neurology. 88(16_supplement).
16.
Hacker, Mallory L., et al.. (2017). Subthalamic Nucleus Deep Brain Stimulation in Early Stage Parkinson’s Disease Is Not Associated with Increased Body Mass Index. Parkinson s Disease. 2017. 1–4. 7 indexed citations
17.
Heusinkveld, Lauren E., Mallory L. Hacker, Maxim Turchan, et al.. (2016). Patient Perspectives on Deep Brain Stimulation Clinical Research in Early Stage Parkinson’s Disease. Journal of Parkinson s Disease. 7(1). 89–94. 11 indexed citations
18.
Hacker, Mallory L., Amanda Currie, Anna Lia Molinari, et al.. (2016). Subthalamic Nucleus Deep Brain Stimulation May Reduce Medication Costs in Early Stage Parkinson’s Disease. Journal of Parkinson s Disease. 6(1). 125–131. 24 indexed citations
19.
Hacker, Mallory L., James Tonascia, Maxim Turchan, et al.. (2015). Deep brain stimulation may reduce the relative risk of clinically important worsening in early stage Parkinson's disease. Parkinsonism & Related Disorders. 21(10). 1177–1183. 33 indexed citations
20.
Earls, Laurie R., Mallory L. Hacker, Joseph D. Watson, & David M. Miller. (2010). Coenzyme Q protects Caenorhabditis elegans GABA neurons from calcium-dependent degeneration. Proceedings of the National Academy of Sciences. 107(32). 14460–14465. 32 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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