Eva Ignatious

688 citations
6 papers · 411 · 1 hit paper · h-index 5

Impact in

Papers in

Eva Ignatious

6 papers receiving 386 citations

Eva Ignatious's Hit Papers

Efficient Prediction of Cardiovascular Disease Using Machine Learning Algorithms With Relief and LASSO Feature Selection Techniques 2021 · 341 citations
3410+1+3Years since publication100200300

Peers

Eva Ignatious
Comparison fields: 5 of 103
  • Health Information Management 223
  • Medical Laboratory Technology 18
  • Health Informatics 11
  • Artificial Intelligence 152
  • Cardiology and Cardiovascular Medicine 64
Replace Shahana Shultana with:
Shahana Shultana Bangladesh
Md. Mamun Ali Canada
Abhijith Reddy Beeravolu Australia
Anna Karen Gárate-Escamilla France
Devansh Shah India
Pooja Rani India
Yar Muhammad Pakistan
Atiqur Rahman Malaysia
Nada Ahmed Saudi Arabia
Oumaima Terrada Morocco
Eva Ignatious relative to Shahana Shultana Bangladesh Shahana Shultana's profile →
Citations per field
00.5×1.5×
Shahana Shultana · 1×
Citations per year

Countries citing papers authored by Eva Ignatious

Since Specialization
Citations

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

Fields of papers citing papers by Eva Ignatious

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 9 scholars most cited alongside Eva Ignatious, 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 Eva Ignatious Line = papers co-authored together Eva Ignatious links everyone, so they are left out of the graph.

All Works

About Eva Ignatious

Eva Ignatious is a scholar working on Cognitive Neuroscience, Health Information Management, Speech and Hearing, Artificial Intelligence and Clinical Psychology, having authored 6 papers that have together received 411 indexed citations. Recurring topics across this work include Hearing Loss and Rehabilitation (3 papers), Artificial Intelligence in Healthcare (2 papers), Noise Effects and Management (2 papers), Neural dynamics and brain function (2 papers), Neuroscience and Music Perception (2 papers), Machine Learning in Healthcare (2 papers), Imbalanced Data Classification Techniques (1 paper) and Suicide and Self-Harm Studies (1 paper). The work is most often cited by research in Health Information Management (223 citations), Medical Laboratory Technology (18 citations), Health Informatics (11 citations), Artificial Intelligence (152 citations) and Cardiology and Cardiovascular Medicine (64 citations). Eva Ignatious has collaborated with scholars based in Australia, Bangladesh and India. Frequent co-authors include Sami Azam, Friso De Boer, Mirjam Jonkman, Abhijith Reddy Beeravolu, Asif Karim, Shahana Shultana, F. M. Javed Mehedi Shamrat, Pronab Ghosh and Md. Mehedi Hassan. Their work appears in journals such as IEEE Access, Journal of Clinical Medicine and Procedia Computer Science.

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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