Swetha Tanamala

1.1k total citations · 1 hit paper
8 papers, 662 citations indexed

About

Swetha Tanamala is a scholar working on Epidemiology, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Swetha Tanamala has authored 8 papers receiving a total of 662 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Epidemiology, 3 papers in Pulmonary and Respiratory Medicine and 3 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Swetha Tanamala's work include Acute Ischemic Stroke Management (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Artificial Intelligence in Healthcare and Education (2 papers). Swetha Tanamala is often cited by papers focused on Acute Ischemic Stroke Management (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Artificial Intelligence in Healthcare and Education (2 papers). Swetha Tanamala collaborates with scholars based in United States, India and Netherlands. Swetha Tanamala's co-authors include Sasank Chilamkurthy, Vidur Mahajan, Prashant Warier, Pooja Rao, Norbert G. Campeau, Vasantha Kumar Venugopal, Rohit Ghosh, Hema A. Murthy, Efstathios Papavassiliou and Santiago Gomez‐Paz and has published in prestigious journals such as The Lancet, Journal of the Neurological Sciences and Academic Radiology.

In The Last Decade

Swetha Tanamala

6 papers receiving 644 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Deep learning algorithms for detection of critical findings in head CT scans: a retrospective study

2018 626 citations Sasank Chilamkurthy, Rohit Ghosh et al. The Lancet profile →

Peers

Swetha Tanamala

RNMI

AI

NEURO

EPIDE

HI

Sasank Chilamkurthy United States

Vidur Mahajan India

Vasantha Kumar Venugopal India

Prashant Warier United States

Myeongchan Kim South Korea

Sehyo Yune South Korea

Javin Schefflein United States

Mohammad Mansouri United States

Michelle Livne Germany

Soichiro Miki Japan

Sasank Chilamkurthy United States

Swetha Tanamala

268 ×0.9

RNMI

184 ×1.0

AI

176 ×1.0

NEURO

161 ×1.0

EPIDE

132 ×0.9

HI

Citations per year, relative to Swetha Tanamala Swetha Tanamala (= 1×) peers Sasank Chilamkurthy

Countries citing papers authored by Swetha Tanamala

Since Specialization

Citations

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

Fields of papers citing papers by Swetha Tanamala

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Swetha Tanamala

This figure shows the co-authorship network connecting the top 25 collaborators of Swetha Tanamala. A scholar is included among the top collaborators of Swetha Tanamala based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Swetha Tanamala. Swetha Tanamala is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Tanamala, Swetha, et al.. (2025). Cross-validation of an artificial intelligence tool for fracture classification and localization on conventional radiography in Dutch population. Insights into Imaging. 16(1). 150–150.

2.

Tanamala, Swetha, et al.. (2024). Effect of Artificial Intelligence as a Second Reader on the Lung Nodule Detection and Localization Accuracy of Radiologists and Non-radiology Physicians in Chest Radiographs: A Multicenter Reader Study. Academic Radiology. 32(3). 1706–1717. 6 indexed citations

3.

Golla, Satish, et al.. (2023). Mind the Clot: Automated LVO Detection on CTA using Deep Learning. 2495–2504. 3 indexed citations

4.

Tanamala, Swetha, et al.. (2022). Role of an Automated Deep Learning Algorithm for Reliable Screening of Abnormality in Chest Radiographs: A Prospective Multicenter Quality Improvement Study. Diagnostics. 12(11). 2724–2724. 14 indexed citations

5.

Maragkos, Georgios Α., Aristotelis Filippidis, Sasank Chilamkurthy, et al.. (2021). Automated Lateral Ventricular and Cranial Vault Volume Measurements in 13,851 Patients Using Deep Learning Algorithms. World Neurosurgery. 148. e363–e373. 7 indexed citations

6.

Webster, Jemin, et al.. (2021). AI improves stroke diagnosis and care at a low resource hospital in India. Journal of the Neurological Sciences. 429. 119660–119660. 1 indexed citations

7.

Chilamkurthy, Sasank, Rohit Ghosh, Swetha Tanamala, et al.. (2018). Deep learning algorithms for detection of critical findings in head CT scans: a retrospective study. The Lancet. 392(10162). 2388–2396. 626 indexed citations breakdown →

8.

Tanamala, Swetha, et al.. (2017). A semi-automatic method for transcription error correction for Indian language TTS systems. 1–6. 5 indexed citations

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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