Deep Patel

42 papers receiving 565 citations

Peers

Deep Patel
Comparison fields: 5 of 112
  • Pulmonary and Respiratory Medicine 192
  • Safety, Risk, Reliability and Quality 59
  • Transportation 30
  • Neurology 58
  • Radiation 31
Replace Kari M. Rosenkranz with:
Kari M. Rosenkranz United States
Chirag Shah United States
Sujata M. Patil United States
Sofie Verbeke Belgium
Nicholas Chan United States
Aiyuan Xie United States
Christina Wagner United States
Christopher M. Byrne Australia
María del Rosario Pérez Switzerland
Daniel Suh United States
Deep Patel relative to Kari M. Rosenkranz United States Kari M. Rosenkranz's profile →
Citations per field
00.5×8.3×
Kari M. Rosenkranz · 1×
Citations per year

Countries citing papers authored by Deep Patel

Since Specialization
Citations

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

Fields of papers citing papers by Deep Patel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Deep Patel, 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 Deep Patel Line = papers co-authored together Deep Patel links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200579
2 200771
3 201653
4 200548
5 198444
6 201834
7 201129
8 202325
9 202224
10 200523
11 198823
12 202217
13 202312
14 201312
15 20237
16 20236
17 20226
18 20236
19 20246
20
Evaluating the effectiveness of the pedestrian safety intervention program: Behavioral and observational approach
20206

About Deep Patel

Deep Patel is a scholar working on Safety, Risk, Reliability and Quality, Pulmonary and Respiratory Medicine, Epidemiology, Transportation and Automotive Engineering, having authored 48 papers that have together received 588 indexed citations. Recurring topics across this work include Traffic and Road Safety (12 papers), Urban Transport and Accessibility (5 papers), Human-Automation Interaction and Safety (4 papers), Traffic Prediction and Management Techniques (4 papers), Autonomous Vehicle Technology and Safety (3 papers), Prostate Cancer Diagnosis and Treatment (3 papers), Transportation Planning and Optimization (2 papers) and Prostate Cancer Treatment and Research (2 papers). The work is most often cited by research in Pulmonary and Respiratory Medicine (192 citations), Safety, Risk, Reliability and Quality (59 citations), Transportation (30 citations), Neurology (58 citations) and Radiation (31 citations). Deep Patel has collaborated with scholars based in United States, Canada and India. Frequent co-authors include Mohammad Jalayer, Christopher R. King, John E. McNeal, Joseph C. Presti, James D. Brooks, Harcharan Gill, L. R. Caplan, Pinakin Arun Karpe, Vajir Malek and Kulbhushan Tikoo. Their work appears in journals such as Accident Analysis & Prevention, Journal of the American Academy of Dermatology, Neurology, Journal of Clinical Oncology and Transportation Research Part F Traffic Psychology and Behaviour.

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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