Inês Machado Vaz

633 citations
25 papers · 276 indexed · h-index 8

Inês Machado Vaz

22 papers receiving 263 citations

Peers

Inês Machado Vaz
Comparison fields: 5 of 85
  • Archeology 37
  • Archeology 70
  • Paleontology 37
  • General Dentistry 8
  • Orthodontics 16
Replace R. J. M. Herd with:
R. J. M. Herd United Kingdom
İşık Tuncer Türkiye
Gail H. Davila United States
Hamid Jalalzadeh Netherlands
Eduard Winter Austria
Erin K. Hatt United States
Maged Ragab Egypt
Chad A. Zarse United States
Joong Seok Seo South Korea
Richard L. Hutchison United States
Inês Machado Vaz relative to R. J. M. Herd United Kingdom R. J. M. Herd's profile →
Citations per field
00.5×8.7×
R. J. M. Herd · 1×
Citations per year

Countries citing papers authored by Inês Machado Vaz

Since Specialization
Citations

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

Fields of papers citing papers by Inês Machado Vaz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Inês Machado Vaz. 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 Inês Machado Vaz. The network helps show where Inês Machado Vaz may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20232
3 20230
4 20221
5 202221
6 20224
7 20211
8 20201
9 202017
10 20205
11 202015
12
EAVOCZ: Escala de apreciação da voz cantada
20181
13 20162
14 20130
15
[Psychosocial characterization of a Portuguese lower limb amputee population].
201311
16 20122
17 201253
18 20111
19 201121
20 201069

About Inês Machado Vaz

Inês Machado Vaz is a scholar working on Critical Care and Intensive Care Medicine, Health Informatics and General Dentistry, having authored 25 papers that have together received 276 indexed citations. Recurring topics across this work include Intensive Care Unit Cognitive Disorders (4 papers), Long-Term Effects of COVID-19 (4 papers), Respiratory Support and Mechanisms (3 papers), Cultural Heritage Materials Analysis (2 papers), Stroke Rehabilitation and Recovery (2 papers), Anesthesia and Pain Management (2 papers), Cardiac, Anesthesia and Surgical Outcomes (2 papers) and Health Systems, Economic Evaluations, Quality of Life (2 papers). The work is most often cited by research in Archeology (37 citations), Archeology (70 citations) and Paleontology (37 citations). Inês Machado Vaz has collaborated with scholars based in Portugal, Switzerland and United States. Frequent co-authors include Eric P. Winer, Nancy U. Lin, Rui J. C. Silva, M. Fátima Araújo, Elin Figueiredo, Francisco Manuel Braz Fernandes, Afonso Rocha, Andreas R. Günthert, Florian Oehme and João Carlos Winck. Their work appears in journals such as SHILAP Revista de lepidopterología, Annals of Oncology and Nutrients.

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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