William Wasswa

1.0k total citations · 1 hit paper
23 papers, 524 citations indexed

About

William Wasswa is a scholar working on Artificial Intelligence, Epidemiology and Computer Vision and Pattern Recognition. According to data from OpenAlex, William Wasswa has authored 23 papers receiving a total of 524 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 6 papers in Epidemiology and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in William Wasswa's work include AI in cancer detection (7 papers), Digital Imaging for Blood Diseases (4 papers) and Cervical Cancer and HPV Research (3 papers). William Wasswa is often cited by papers focused on AI in cancer detection (7 papers), Digital Imaging for Blood Diseases (4 papers) and Cervical Cancer and HPV Research (3 papers). William Wasswa collaborates with scholars based in Uganda, United Kingdom and United States. William Wasswa's co-authors include Annabella Habinka Basaza‐Ejiri, Johnes Obungoloch, Andrew Ware, Lita Chew, Atul J. Butte, Nan Liu, Daniel Shu Wei Ting, Finale Doshi‐Velez, Nigam H. Shah and Yin‐Hsi Chang and has published in prestigious journals such as Science, SHILAP Revista de lepidopterología and Nature Methods.

In The Last Decade

William Wasswa

21 papers receiving 507 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.

Ethical and regulatory challenges of large language models in medicine

2024 105 citations Jasmine Chiat Ling Ong, Yin‐Hsi Chang et al. The Lancet Digital Health profile →

Peers

William Wasswa

AI

EPIDE

RNMI

HI

CVPR

Karthik V. Sarma United States

Colin B. Compas United States

Azamossadat Hosseini Iran

Niels Olson United States

Friederike Jungmann Germany

Lin Guo China

Khalid Gaffer Mohamed Saudi Arabia

Surabhi Datta United States

Xiaoming Qiu China

Chaoyi Wu China

Karthik V. Sarma United States

William Wasswa

242 ×0.7

AI

51 ×0.3

EPIDE

186 ×1.5

RNMI

41 ×0.4

HI

80 ×0.8

CVPR

Citations per year, relative to William Wasswa William Wasswa (= 1×) peers Karthik V. Sarma

Countries citing papers authored by William Wasswa

Since Specialization

Citations

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

Fields of papers citing papers by William Wasswa

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of William Wasswa

This figure shows the co-authorship network connecting the top 25 collaborators of William Wasswa. A scholar is included among the top collaborators of William Wasswa 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 William Wasswa. William Wasswa 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:

20 of 20 papers shown

1.

Musiimenta, Angella, et al.. (2025). A neonatal sepsis prediction algorithm using electronic medical record data from Mbarara Regional Referral Hospital. Intelligence-Based Medicine. 11. 100198–100198. 1 indexed citations

2.

Wasswa, William, et al.. (2025). Deep Learning Techniques in DICOM Files Classification: A Systematic Review.

3.

Ong, Jasmine Chiat Ling, Yin‐Hsi Chang, William Wasswa, et al.. (2024). Ethical and regulatory challenges of large language models in medicine. The Lancet Digital Health. 6(6). e428–e432. 105 indexed citations breakdown →

4.

Wasswa, William. (2024). Automated innovation and impact. Science. 384(6691). 42–42. 2 indexed citations

5.

Ong, Jasmine Chiat Ling, Yin‐Hsi Chang, William Wasswa, et al.. (2024). Medical Ethics of Large Language Models in Medicine. NEJM AI. 1(7). 23 indexed citations

6.

Wasswa, William, et al.. (2023). Legacy of COVID-19 Innovations: Strengthening African Primary Health Care through Pandemic Innovations. Sustainability. 15(15). 12073–12073. 1 indexed citations

7.

Charpignon, Marie‐Laure, Joseph T. Byers, Stephanie Cabral, et al.. (2023). Critical Bias in Critical Care Devices. Critical Care Clinics. 39(4). 795–813. 19 indexed citations

8.

Wasswa, William, et al.. (2023). Scaling up delivery of HIV services in Africa through harnessing trends across global emerging innovations. SHILAP Revista de lepidopterología. 3. 1198008–1198008. 1 indexed citations

9.

Simegn, Gizeaddis Lamesgin, et al.. (2023). Unveiling the vision: exploring the potential of image analysis in Africa. Nature Methods. 20(7). 979–981. 1 indexed citations

10.

Wasswa, William, et al.. (2023). Leveraging innovation technologies to respond to malaria: a systematized literature review of emerging technologies. Malaria Journal. 22(1). 40–40. 11 indexed citations

11.

Zhang, Joe, Sanjay Budhdeo, William Wasswa, et al.. (2022). Moving towards vertically integrated artificial intelligence development. npj Digital Medicine. 5(1). 143–143. 21 indexed citations

12.

Yan, Tingting, Michael Lang, Teddy Kyomuhangi, et al.. (2021). Let all know : insights from a digital storytelling facilitator training in Uganda. Global Health Action. 14(1). 1933786–1933786. 6 indexed citations

13.

Wasswa, William, Andrew Ware, Annabella Habinka Basaza‐Ejiri, & Johnes Obungoloch. (2019). A pap-smear analysis tool (PAT) for detection of cervical cancer from pap-smear images. BioMedical Engineering OnLine. 18(1). 16–16. 76 indexed citations

14.

Wasswa, William, Johnes Obungoloch, Annabella Habinka Basaza‐Ejiri, & Andrew Ware. (2019). Automated Segmentation of Nucleus, Cytoplasm and Background of Cervical Cells from Pap-smear Images using a Trainable Pixel Level Classifier. 1–9. 3 indexed citations

15.

Wasswa, William, Andrew Ware, Annabella Habinka Basaza‐Ejiri, & Johnes Obungoloch. (2019). Automated Diagnosis and Classification of Cervical Cancer from pap-smear Images. 1–11. 6 indexed citations

16.

Wasswa, William, Andrew Ware, Annabella Habinka Basaza‐Ejiri, & Johnes Obungoloch. (2019). Cervical cancer classification from Pap-smears using an enhanced fuzzy C-means algorithm. Informatics in Medicine Unlocked. 14. 23–33. 55 indexed citations

17.

Wasswa, William, Andrew Ware, Annabella Habinka Basaza‐Ejiri, & Johnes Obungoloch. (2018). A review of image analysis and machine learning techniques for automated cervical cancer screening from pap-smear images. Computer Methods and Programs in Biomedicine. 164. 15–22. 181 indexed citations

18.

Wasswa, William, Annabella Habinka Basaza‐Ejiri, Johnes Obungoloch, & Andrew Ware. (2018). A Review of Applications of Image Analysis and Machine Learning Techniques in Automated Diagnosis and Classification of Cervical Cancer from Pap-smear Images. 5 indexed citations

19.

Mutsvangwa, Tinashe, William Wasswa, Valérie Burdin, Bhushan Borotikar, & Tania S. Douglas. (2017). Interactive patient-specific 3D approximation of scapula bone shape from 2D X-ray images using landmark-constrained statistical shape model fitting. PubMed. 2017. 1816–1819. 3 indexed citations

20.

Wasswa, William & Bing Zeng. (2002). Fast texture synthesis by feature matching. 2. 614–617. 2 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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