D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Medicine D-index 77 Citations 25,720 268 World Ranking 11017 National Ranking 5889

Overview

What is he best known for?

The fields of study he is best known for:

  • Internal medicine
  • Radiology
  • Cancer

The scientist’s investigation covers issues in Radiology, Radiography, Nuclear medicine, Computer-aided diagnosis and Medical imaging. His Radiology study integrates concerns from other disciplines, such as Lung cancer, Lung, CAD and Artificial intelligence. The Radiography study combines topics in areas such as Artificial neural network, Thorax, Computed tomography and Receiver operating characteristic.

His Nuclear medicine research incorporates elements of Helical computed tomography, Computed tomographic, False positive paradox, Nodule and Linear discriminant analysis. His Medical imaging study incorporates themes from Medical physics, Image database and Pattern recognition. His Medical physics research is multidisciplinary, incorporating elements of Pulmonologists and Pediatrics.

His most cited work include:

  • Fleischner Society: Glossary of Terms for Thoracic Imaging (2070 citations)
  • Guidelines for Management of Small Pulmonary Nodules Detected on CT Scans: A Statement from the Fleischner Society (1280 citations)
  • The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): a completed reference database of lung nodules on CT scans. (1008 citations)

What are the main themes of his work throughout his whole career to date?

Heber MacMahon spends much of his time researching Radiology, Radiography, Computer-aided diagnosis, Artificial intelligence and Nuclear medicine. His Radiology research incorporates themes from Lung cancer, Lung and Receiver operating characteristic. His work in Radiography addresses issues such as Interstitial lung disease, which are connected to fields such as Artificial neural network.

Image database is closely connected to Medical physics in his research, which is encompassed under the umbrella topic of Computer-aided diagnosis. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Computer vision and Pattern recognition. He has researched Nuclear medicine in several fields, including Thresholding and Computed tomography.

He most often published in these fields:

  • Radiology (46.11%)
  • Radiography (38.02%)
  • Computer-aided diagnosis (19.16%)

What were the highlights of his more recent work (between 2010-2021)?

  • Radiology (46.11%)
  • Lung cancer (11.08%)
  • Radiography (38.02%)

In recent papers he was focusing on the following fields of study:

His primary scientific interests are in Radiology, Lung cancer, Radiography, Lung cancer screening and Nodule. His specific area of interest is Radiology, where Heber MacMahon studies Computed tomography. Heber MacMahon interconnects Cancer and Metastasis in the investigation of issues within Lung cancer.

His study in Radiography is interdisciplinary in nature, drawing from both Artificial intelligence, Medical imaging, Nuclear medicine and Pattern recognition. The study incorporates disciplines such as Contextual image classification, Computer-aided diagnosis and Response assessment in addition to Medical imaging. His Nodule course of study focuses on Pulmonologists and Medical physics, Individual risk factors and Routine clinical practice.

Between 2010 and 2021, his most popular works were:

  • The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): a completed reference database of lung nodules on CT scans. (1008 citations)
  • Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017 (685 citations)
  • Recommendations for the Management of Subsolid Pulmonary Nodules Detected at CT: A Statement from the Fleischner Society (654 citations)

In his most recent research, the most cited papers focused on:

  • Internal medicine
  • Radiology
  • Surgery

His main research concerns Radiology, Lung cancer, Medical physics, Lung and Radiography. His research integrates issues of Cancer, Survival analysis and Proportional hazards model in his study of Radiology. His work investigates the relationship between Lung cancer and topics such as Metastasis that intersect with problems in Malignancy, Magnetic resonance imaging, Tomography and Scintigraphy.

The concepts of his Medical physics study are interwoven with issues in Pulmonologists, Nodule, Pediatrics and Computed tomography. Heber MacMahon combines subjects such as Receiver operating characteristic, Dual energy subtraction and Pathology with his study of Lung. His Radiography research is multidisciplinary, relying on both Computer-aided diagnosis and Medical imaging.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Fleischner Society: Glossary of Terms for Thoracic Imaging

David M Hansell;Alexander A Bankier;Heber MacMahon;Theresa C McLoud.
Radiology (2008)

2981 Citations

Guidelines for Management of Small Pulmonary Nodules Detected on CT Scans: A Statement from the Fleischner Society

Heber MacMahon;John H. M. Austin;Gordon Gamsu;Christian J. Herold.
Radiology (2005)

1769 Citations

The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): a completed reference database of lung nodules on CT scans.

Samuel G. Armato;Geoffrey McLennan;Luc Bidaut;Michael F. McNitt‐Gray.
Medical Physics (2011)

1286 Citations

Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017

Heber MacMahon;David P. Naidich;Jin Mo Goo;Kyung Soo Lee.
Radiology (2017)

1029 Citations

Recommendations for the Management of Subsolid Pulmonary Nodules Detected at CT: A Statement from the Fleischner Society

David P. Naidich;Alexander A. Bankier;Heber MacMahon;Cornelia M. Schaefer-Prokop.
Radiology (2013)

945 Citations

The American Association for Thoracic Surgery guidelines for lung cancer screening using low-dose computed tomography scans for lung cancer survivors and other high-risk groups

Michael T. Jaklitsch;Francine L. Jacobson;John H.M. Austin;John K. Field.
The Journal of Thoracic and Cardiovascular Surgery (2012)

573 Citations

Improvement in radiologists' detection of clustered microcalcifications on mammograms. The potential of computer-aided diagnosis.

H P Chan;K Doi;C J Vyborny;R A Schmidt.
Investigative Radiology (1990)

511 Citations

Computerized Detection of Pulmonary Nodules on CT Scans

Samuel G. Armato;Maryellen L. Giger;Catherine J. Moran;James T. Blackburn.
Radiographics (1999)

509 Citations

Image feature analysis and computer-aided diagnosis in digital radiography. I. Automated detection of microcalcifications in mammography

Heang Ping Chan;Kunio Doi;Simranjit Galhotra;Carl J. Vyborny.
Medical Physics (1987)

492 Citations

Lung image database consortium: developing a resource for the medical imaging research community.

Samuel G. Armato;Geoffrey McLennan;Michael F. McNitt-Gray;Charles R. Meyer.
Radiology (2004)

429 Citations

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