Walker H. Land

576 total citations
56 papers, 412 citations indexed

About

Walker H. Land is a scholar working on Artificial Intelligence, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Walker H. Land has authored 56 papers receiving a total of 412 indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Artificial Intelligence, 28 papers in Molecular Biology and 10 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Walker H. Land's work include Gene expression and cancer classification (25 papers), AI in cancer detection (25 papers) and Radiomics and Machine Learning in Medical Imaging (8 papers). Walker H. Land is often cited by papers focused on Gene expression and cancer classification (25 papers), AI in cancer detection (25 papers) and Radiomics and Machine Learning in Medical Imaging (8 papers). Walker H. Land collaborates with scholars based in United States. Walker H. Land's co-authors include Omowunmi A. Sadik, Joseph Wang, Timothy Masters, Joseph Y. Lo, John Heine, J. David Schaffer, Xingye Qiao, Daniel Margolis, Jack Yang and Daniel McKee and has published in prestigious journals such as Gastroenterology, BMC Bioinformatics and BMC Genomics.

In The Last Decade

Walker H. Land

54 papers receiving 391 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Walker H. Land United States 10 152 123 65 48 47 56 412
Anasua Sarkar India 12 76 0.5× 181 1.5× 52 0.8× 6 0.1× 65 1.4× 48 622
Manisha Guduri India 7 84 0.6× 28 0.2× 131 2.0× 47 1.0× 32 0.7× 27 350
Zijuan Zhao China 9 57 0.4× 105 0.9× 38 0.6× 6 0.1× 21 0.4× 30 305
Haochen Qi China 12 39 0.3× 142 1.2× 125 1.9× 47 1.0× 169 3.6× 39 476
Joseph Wang United States 8 75 0.5× 21 0.2× 61 0.9× 46 1.0× 26 0.6× 16 224
Yasheng Wang China 13 330 2.2× 96 0.8× 43 0.7× 9 0.2× 88 1.9× 48 585
Yanming Wang China 15 42 0.3× 129 1.0× 79 1.2× 15 0.3× 50 1.1× 38 514
Yaqian Li China 8 26 0.2× 61 0.5× 33 0.5× 17 0.4× 33 0.7× 45 327
Jiajin Zhang China 13 88 0.6× 70 0.6× 71 1.1× 4 0.1× 65 1.4× 32 366

Countries citing papers authored by Walker H. Land

Since Specialization
Citations

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

Fields of papers citing papers by Walker H. Land

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Walker H. Land. 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 Walker H. Land. The network helps show where Walker H. Land may publish in the future.

Co-authorship network of co-authors of Walker H. Land

This figure shows the co-authorship network connecting the top 25 collaborators of Walker H. Land. A scholar is included among the top collaborators of Walker H. Land 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 Walker H. Land. Walker H. Land is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Li, Yinglei, et al.. (2016). Automated analysis of food-borne pathogens using a novel microbial cell culture, sensing and classification system. The Analyst. 141(4). 1472–1482. 7 indexed citations
2.
Li, Yinglei, et al.. (2013). Development of a Complex Adaptive PNN System for the Rapid Detection of E.coli. Procedia Computer Science. 20. 342–347. 7 indexed citations
3.
Masters, Timothy, et al.. (2013). A Novel Application for Combining CASs and Datasets to Produce Increased Accuracy in Modeling and Predicting Cancer Recurrence. Procedia Computer Science. 20. 354–359. 3 indexed citations
4.
Land, Walker H., et al.. (2013). Investigating the GRNN Oracle as a Method for Combining Multiple Predictive Models of Colon Cancer Recurrence from Gene Microarrays. Procedia Computer Science. 20. 374–378. 5 indexed citations
5.
Deng, Youping, et al.. (2012). Classifying Lung Cancer Recurrence Time Using Novel Ensemble Method with Gene Network based Input Models. Procedia Computer Science. 12. 444–449. 5 indexed citations
6.
Schaffer, J. David, Jin‐Woo Park, Erin Barnes, et al.. (2012). GRNN Ensemble Classifier for Lung Cancer Prognosis Using Only Demographic and TNM features. Procedia Computer Science. 12. 450–455. 3 indexed citations
7.
Heine, John, Walker H. Land, & Kathleen M. Egan. (2011). Statistical learning techniques applied to epidemiology: a simulated case-control comparison study with logistic regression. BMC Bioinformatics. 12(1). 37–37. 5 indexed citations
8.
Behera, Madhusmita, Taofeek K. Owonikoko, Walker H. Land, et al.. (2011). Statistical learning methods as a preprocessing step for survival analysis: evaluation of concept using lung cancer data. BioMedical Engineering OnLine. 10(1). 97–97. 12 indexed citations
9.
Land, Walker H., Xingye Qiao, Joseph Perez-Rogers, et al.. (2011). Kernelized partial least squares for feature reduction and classification of gene microarray data. BMC Systems Biology. 5(Suppl 3). S13–S13. 17 indexed citations
10.
Land, Walker H., Daniel Margolis, Ronald H. Gottlieb, Elizabeth A. Krupinski, & Jack Yang. (2010). Improving CT prediction of treatment response in patients with metastatic colorectal carcinoma using statistical learning theory. BMC Genomics. 11(Suppl 3). S15–S15. 13 indexed citations
11.
Land, Walker H., et al.. (2009). Multiclass primal Support Vector Machines for breast density classification. International Journal of Computational Biology and Drug Design. 2(1). 21–21. 2 indexed citations
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13.
Land, Walker H., et al.. (2007). Evaluation of two key machine intelligence technologies. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6560. 65600U–65600U. 2 indexed citations
14.
Land, Walker H., et al.. (2005). Applying knowledge engineering and representation methods to improve support vector machine and multivariate probabilistic neural network CAD performance. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5747. 895–895. 1 indexed citations
15.
Land, Walker H., et al.. (2005). New approach to breast cancer CAD using partial least squares and kernel-partial least squares. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5747. 48–48. 2 indexed citations
16.
Sadik, Omowunmi A., et al.. (2004). Detection and Classification of Organophosphate Nerve Agent Simulants Using Support Vector Machines with Multiarray Sensors. Journal of Chemical Information and Computer Sciences. 44(2). 499–507. 29 indexed citations
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Land, Walker H., et al.. (2001). <title>Application of adaptive boosting to EP-derived multilayer feed-forward neural networks (MLFN) to improve benign/malignant breast cancer classification</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 4322. 1717–1724. 4 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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