Hani Malone

1.7k citations
32 papers · 1.1k · h-index 13

Impact in

Papers in

Hani Malone

31 papers receiving 1.1k citations

Peers

Hani Malone
Comparison fields: 5 of 86
  • Genetics 407
  • Endocrinology, Diabetes and Metabolism 133
  • Cancer Research 110
  • Neurology 94
  • Radiology, Nuclear Medicine and Imaging 135
Replace Song Lin with:
Song Lin China
Rajiv Magge United States
Pedro David Delgado‐López Spain
Takao Fukushima Japan
Makoto Shibuya Japan
Hannah E. Goldstein United States
Shingo Tanaka Japan
Manuela Caroli Italy
Jennifer Moliterno United States
Marcel Seiz Germany
Hani Malone relative to Song Lin China Song Lin's profile →
Citations per field
00.5×2.8×
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Citations per year

Countries citing papers authored by Hani Malone

Since Specialization
Citations

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

Fields of papers citing papers by Hani Malone

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Hani Malone, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Hani Malone Line = papers co-authored together Hani Malone links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014202
2 2010149
3 2012141
4 2016127
5 2015113
6 201789
7 201462
8 201537
9 201530
10 201728
11 201723
12 201716
13 201212
14 201312
15 202111
16 201311
17 201310
18 20229
19 20199
20 20218

About Hani Malone

Hani Malone is a scholar working on Surgery, Pathology and Forensic Medicine, Genetics, Pulmonary and Respiratory Medicine and Epidemiology, having authored 32 papers that have together received 1.1k indexed citations. Recurring topics across this work include Spine and Intervertebral Disc Pathology (9 papers), Spinal Fractures and Fixation Techniques (6 papers), Glioma Diagnosis and Treatment (6 papers), Cerebrovascular and Carotid Artery Diseases (3 papers), Surgical Simulation and Training (2 papers), Intracranial Aneurysms: Treatment and Complications (2 papers), Acute Ischemic Stroke Management (2 papers) and Medical Imaging and Analysis (2 papers). The work is most often cited by research in Genetics (407 citations), Endocrinology, Diabetes and Metabolism (133 citations), Cancer Research (110 citations), Neurology (94 citations) and Radiology, Nuclear Medicine and Imaging (135 citations). Hani Malone has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Jeffrey N. Bruce, Alfred I. Neugut, Peter Canoll, Hannah E. Goldstein, Michael B. Sisti, Anthony D’Ambrosio, Guy M. McKhann, Donald O. Quest, Michael G. Kaiser and Michael S. Downes. Their work appears in journals such as Neurosurgery, Journal of neurosurgery, Journal of Neurosurgery Spine, World Neurosurgery and Neuro-Oncology.

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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