Diagnostics

13.9k papers and 104.3k indexed citations
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About

The 13.9k papers published in Diagnostics in the last decades have received a total of 104.3k indexed citations. Papers published in Diagnostics usually cover Radiology, Nuclear Medicine and Imaging (3.1k papers), Surgery (2.8k papers) and Pulmonary and Respiratory Medicine (2.6k papers) specifically the topics of Radiomics and Machine Learning in Medical Imaging (1.0k papers), AI in cancer detection (615 papers) and COVID-19 diagnosis using AI (427 papers). The most active scholars publishing in Diagnostics are Sandeep Kumar Vashist, Omneya Attallah, Reabal Najjar, Robertas Damaševičius, Oke Gerke, Michael Bachmann Nielsen, Muhammad Attique Khan, Frederick R. Ueland, Mohd Farhan Siddiqui and Seungkyung Park.

In The Last Decade

Diagnostics

11.6k papers receiving 98.1k citations

Fields of papers published in Diagnostics

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Diagnostics. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Diagnostics.

Countries where authors publish in Diagnostics

Since Specialization
Citations

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

Cloud Computing-Based Framework for Breast Cancer Diagnosis Using Extreme Learning Machine 2021 2026 2022 2024114
  1. Cloud Computing-Based Framework for Breast Cancer Diagnosis Using Extreme Learning Machine (2021)

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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