D-Index & Metrics Best Publications

D-Index & Metrics 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.

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
Computer Science D-index 64 Citations 16,363 269 World Ranking 1624 National Ranking 902

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Internal medicine
  • Statistics

His primary scientific interests are in Artificial intelligence, Pattern recognition, Data mining, Electrocardiography and Speech recognition. His work in the fields of Artificial intelligence, such as Test set, intersects with other areas such as Noise. His Pattern recognition research is multidisciplinary, incorporating perspectives in Waveform, Noise and Signal processing.

He studied Electrocardiography and Kalman filter that intersect with Artifact. His Speech recognition research incorporates elements of Healthy subjects, Segmentation and Heart sounds. His research integrates issues of Algorithm and Database in his study of Heart valve.

His most cited work include:

  • A dynamical model for generating synthetic electrocardiogram signals (841 citations)
  • Multiparameter Intelligent Monitoring in Intensive Care II: a public-access intensive care unit database. (698 citations)
  • Multiparameter Intelligent Monitoring in Intensive Care II: a public-access intensive care unit database. (698 citations)

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

Gari D. Clifford mostly deals with Artificial intelligence, Pattern recognition, Internal medicine, Cardiology and Speech recognition. The Artificial intelligence study combines topics in areas such as Electrocardiography, Machine learning and Signal. The study incorporates disciplines such as QRS complex, Noise and Signal processing in addition to Pattern recognition.

His research on QRS complex frequently connects to adjacent areas such as Algorithm. In his study, Receiver operating characteristic is strongly linked to Heart rate, which falls under the umbrella field of Cardiology. His Speech recognition research integrates issues from Segmentation and Heart sounds.

He most often published in these fields:

  • Artificial intelligence (35.84%)
  • Pattern recognition (24.81%)
  • Internal medicine (21.55%)

What were the highlights of his more recent work (between 2019-2021)?

  • Internal medicine (21.55%)
  • Artificial intelligence (35.84%)
  • Cardiology (21.05%)

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

His primary areas of investigation include Internal medicine, Artificial intelligence, Cardiology, Clinical psychology and Pattern recognition. His work on Cohort, Critical congenital heart disease and Cardiogenic shock is typically connected to Coarctation of the aorta as part of general Internal medicine study, connecting several disciplines of science. His Artificial intelligence research is multidisciplinary, relying on both Smoothing, Machine learning and Electroencephalography.

As part of the same scientific family, Gari D. Clifford usually focuses on Cardiology, concentrating on Metric and intersecting with Generalizability theory and Medical diagnosis. He combines subjects such as Heart rate variability, Multifunction cardiogram, Beat and McNemar's test with his study of Pattern recognition. As part of one scientific family, Gari D. Clifford deals mainly with the area of Test set, narrowing it down to issues related to the Early prediction, and often Algorithm.

Between 2019 and 2021, his most popular works were:

  • Early Prediction of Sepsis From Clinical Data: The PhysioNet/Computing in Cardiology Challenge 2019. (77 citations)
  • Early Prediction of Sepsis From Clinical Data: The PhysioNet/Computing in Cardiology Challenge 2019. (77 citations)
  • Classification of 12-lead ECGs: the PhysioNet/Computing in Cardiology Challenge 2020. (57 citations)

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

  • Internal medicine
  • Artificial intelligence
  • Statistics

His scientific interests lie mostly in Cardiology, Internal medicine, Metric, Generalizability theory and Medical diagnosis. His biological study focuses on Heart failure. Internal medicine is frequently linked to Photoplethysmogram in his study.

His study in Generalizability theory is interdisciplinary in nature, drawing from both Psychological intervention, Severity of illness, Public health and Sepsis. His biological study spans a wide range of topics, including Posttraumatic stress, Neuroimaging and Identification. His research integrates issues of Real-time computing, Triage and Receiver operating characteristic in his study of Identification.

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

A dynamical model for generating synthetic electrocardiogram signals

P.E. McSharry;G.D. Clifford;L. Tarassenko;L.A. Smith.
IEEE Transactions on Biomedical Engineering (2003)

1374 Citations

Multiparameter Intelligent Monitoring in Intensive Care II: a public-access intensive care unit database.

Mohammed Saeed;Mauricio Villarroel;Andrew T. Reisner;Gari Clifford;Gari Clifford.
Critical Care Medicine (2011)

1102 Citations

Advanced Methods And Tools for ECG Data Analysis

Gari D. Clifford;Francisco Azuaje;Patrick McSharry.
(2006)

1091 Citations

A Nonlinear Bayesian Filtering Framework for ECG Denoising

R. Sameni;M.B. Shamsollahi;C. Jutten;G.D. Clifford.
IEEE Transactions on Biomedical Engineering (2007)

569 Citations

AF classification from a short single lead ECG recording: The PhysioNet/computing in cardiology challenge 2017

Gari D Clifford;Chengyu Liu;Benjamin Moody;Li-wei H. Lehman.
computing in cardiology conference (2017)

426 Citations

A Review of Fetal ECG Signal Processing; Issues and Promising Directions.

Reza Sameni;Gari D. Clifford.
The Open Pacing, Electrophysiology & Therapy Journal (2010)

415 Citations

Automated de-identification of free-text medical records

Ishna Neamatullah;Margaret M Douglass;Li-wei H Lehman;Andrew Tomas Reisner.
BMC Medical Informatics and Decision Making (2008)

413 Citations

Robust heart rate estimation from multiple asynchronous noisy sources using signal quality indices and a Kalman filter.

Q Li;R G Mark;G D Clifford.
Physiological Measurement (2008)

399 Citations

An open access database for the evaluation of heart sound algorithms.

Chengyu Liu;David Springer;Qiao Li;Benjamin Moody.
Physiological Measurement (2016)

393 Citations

Logistic Regression-HSMM-Based Heart Sound Segmentation

David B. Springer;Lionel Tarassenko;Gari D. Clifford.
IEEE Transactions on Biomedical Engineering (2016)

327 Citations

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