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Anant Madabhushi

Anant Madabhushi

D-Index & Metrics

Computer Science

D-Index
87
Citations
38549
World Ranking
707
National Ranking
372

Research.com Recognitions

  • 2020 - Fellow, National Academy of Inventors
  • 2015 - Fellow of the Indian National Academy of Engineering (INAE)

Overview

Anant Madabhushi is affiliated with Emory University in the United States. Their research spans medicine with a strong focus on medical imaging, radiology, oncology, and artificial intelligence applications in healthcare.

The scientist's main fields of study include:

  • Medicine

Within medicine, Madabhushi's subfields of study involve:

  • Radiology, Nuclear Medicine and Imaging
  • Pulmonary and Respiratory Medicine
  • Oncology
  • Artificial Intelligence
  • Surgery

Key topics within their research portfolio cover:

  • Radiomics and Machine Learning in Medical Imaging
  • AI in cancer detection
  • Lung Cancer Diagnosis and Treatment
  • Cancer Immunotherapy and Biomarkers
  • Prostate Cancer Diagnosis and Treatment
  • Advanced X-ray and CT Imaging
  • Head and Neck Cancer Studies

Recent papers authored or coauthored by Anant Madabhushi include:

  • "Predicting cancer outcomes with radiomics and artificial intelligence in radiology," 2021, Nature Reviews Clinical Oncology
  • "Digital pathology and computational image analysis in nephropathology," 2020, Nature Reviews Nephrology
  • "Artificial Intelligence and Machine Learning in Arrhythmias and Cardiac Electrophysiology," 2020, Circulation Arrhythmia and Electrophysiology
  • "Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update," 2024, Radiology Artificial Intelligence
  • "Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer," 2020, npj Breast Cancer

Madabhushi collaborates frequently with several coauthors including:

  • Pingfu Fu
  • Kaustav Bera
  • Vidya Sankar Viswanathan
  • Germán Corredor
  • Andrew Janowczyk

The researcher has published extensively in venues such as:

  • Cancer Research
  • Journal of Clinical Oncology
  • Journal of the American Society of Nephrology
  • Circulation
  • Regular and Young Investigator Award Abstracts

In addition to journal articles, Madabhushi has contributed to book literature, with a publication titled "Multimodal Learning for Clinical Decision Support" released by Springer Science+Business Media in 2021.

Throughout their career, Anant Madabhushi has been recognized with awards including:

  • Fellow, National Academy of Inventors (2020)
  • Fellow of the Indian National Academy of Engineering (INAE) (2015)

Best Publications

  • Applications of machine learning in drug discovery and development.

    Jessica Vamathevan;Dominic Clark;Paul Czodrowski;Ian Dunham

  • Histopathological Image Analysis: A Review

    M.N. Gurcan;L.E. Boucheron;A. Can;A. Madabhushi

  • A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies With Progress Highlights, and Future Promises

    S. Kevin Zhou;Hayit Greenspan;Christos Davatzikos;James S. Duncan

  • Artificial intelligence in digital pathology — new tools for diagnosis and precision oncology

    Kaustav Bera;Kurt A. Schalper;David L. Rimm;Vamsidhar Velcheti

  • Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases.

    Andrew Janowczyk;Anant Madabhushi

  • Image analysis and machine learning in digital pathology: Challenges and opportunities

    Anant Madabhushi;George Lee

  • Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images

    Jun Xu;Lei Xiang;Qingshan Liu;Hannah Gilmore

  • Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge.

    Geert J. S. Litjens;Robert Toth;Wendy J. M. van de Ven;Caroline Hoeks

  • Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

    M. Jorge Cardoso;Tal Arbel;Gustavo Carneiro;Tanveer Syeda-Mahmood

  • Predicting cancer outcomes with radiomics and artificial intelligence in radiology.

    Kaustav Bera;Kaustav Bera;Nathaniel Braman;Amit Gupta;Amit Gupta;Vamsidhar Velcheti

  • Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks

    Angel Cruz-Roa;Ajay Basavanhally;Fabio González;Hannah Leah Gilmore

  • Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI

    Nathaniel M. Braman;Maryam Etesami;Prateek Prasanna;Christina Dubchuk

  • Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent

    Angel Cruz-Roa;Angel Cruz-Roa;Hannah Leah Gilmore;Ajay Basavanhally;Michael Feldman

  • Assessment of algorithms for mitosis detection in breast cancer histopathology images

    Mitko Veta;Paul J. van Diest;Stefan M. Willems;Haibo Wang

  • A Deep Convolutional Neural Network for segmenting and classifying epithelial and stromal regions in histopathological images.

    Jun Xu;Xiaofei Luo;Guanhao Wang;Hannah Leah Gilmore

  • Digital imaging in pathology: whole-slide imaging and beyond.

    Farzad Ghaznavi;Andrew Evans;Anant Madabhushi;Michael Feldman

  • A deep learning architecture for image representation, visual interpretability and automated basal-cell carcinoma cancer detection.

    Angel Alfonso Cruz-Roa;John Edison Arevalo Ovalle;Anant Madabhushi;Fabio Augusto González Osorio

  • Automated gland and nuclei segmentation for grading of prostate and breast cancer histopathology

    S. Naik;S. Doyle;S. Agner;A. Madabhushi

  • Combining low-, high-level and empirical domain knowledge for automated segmentation of ultrasonic breast lesions

    A. Madabhushi;D.N. Metaxas

  • Mitosis detection in breast cancer pathology images by combining handcrafted and convolutional neural network features

    Haibo Wang;Angel Cruz-Roa;Ajay Basavanhally;Hannah Leah Gilmore

Frequent Co-Authors

Shridar Ganesan
Shridar Ganesan Rutgers, The State University of New Jersey
Fabio A. González
Fabio A. González National University of Colombia
Metin N. Gurcan
Metin N. Gurcan Wake Forest University
Kurt A. Schalper
Kurt A. Schalper Yale University
Dimitris N. Metaxas
Dimitris N. Metaxas Rutgers, The State University of New Jersey
Dean C. Barratt
Dean C. Barratt University College London
Jayaram K. Udupa
Jayaram K. Udupa University of Pennsylvania
Geert Litjens
Geert Litjens Radboud University

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