2018 - IEEE Fellow For contributions to medical diagnostic and mobile health systems
Constantinos S. Pattichis mostly deals with Artificial intelligence, Ultrasound, Computer vision, Pattern recognition and Image texture. His Artificial intelligence study frequently intersects with other fields, such as Machine learning. Constantinos S. Pattichis interconnects Stroke, Segmentation, Asymptomatic and Normalization in the investigation of issues within Ultrasound.
His work deals with themes such as Ultrasound imaging and Medical imaging, which intersect with Computer vision. His Pattern recognition research is multidisciplinary, incorporating elements of Speech recognition, Signal, Signal processing and Receiver operating characteristic. He combines subjects such as Classifier, Feature and Unsupervised learning with his study of Artificial neural network.
Artificial intelligence, Computer vision, Pattern recognition, Ultrasound and Artificial neural network are his primary areas of study. Many of his studies on Artificial intelligence apply to Machine learning as well. His biological study spans a wide range of topics, including Ultrasound imaging and Medical imaging.
The various areas that Constantinos S. Pattichis examines in his Pattern recognition study include Speech recognition and Feature. His Ultrasound study combines topics from a wide range of disciplines, such as Stroke, Asymptomatic and Carotid arteries, Common carotid artery. His work carried out in the field of Artificial neural network brings together such families of science as Unsupervised learning and Feature.
Constantinos S. Pattichis mainly focuses on Artificial intelligence, Magnetic resonance imaging, Multimedia, Ultrasound and Data science. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning, Descriptive knowledge and Computer vision. In the field of Computer vision, his study on 3D reconstruction overlaps with subjects such as Interval.
His Multimedia research is multidisciplinary, incorporating elements of Systems medicine, Real-time computing, Co-creation, Video quality and Virtual reality. Constantinos S. Pattichis has included themes like Internal carotid artery, Internal medicine and Common carotid artery in his Ultrasound study. Constantinos S. Pattichis has researched Data science in several fields, including Precision medicine and World Wide Web.
His scientific interests lie mostly in Data science, Video quality, Precision medicine, Artificial intelligence and Mediterranean climate. His studies in Data science integrate themes in fields like Domain and General Data Protection Regulation. His study in Video quality is interdisciplinary in nature, drawing from both Data compression, Real-time computing and Multimedia.
Constantinos S. Pattichis usually deals with Multimedia and limits it to topics linked to Coding and Ultrasound and Telemedicine. His study looks at the relationship between Precision medicine and topics such as Big data, which overlap with Open data and Knowledge extraction. Many of his studies on Artificial intelligence involve topics that are commonly interrelated, such as Machine learning.
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.
Wireless telemedicine systems: an overview
C.S. Pattichis;E. Kyriacou;S. Voskarides;M.S. Pattichis.
IEEE Antennas and Propagation Magazine (2002)
Texture-based classification of atherosclerotic carotid plaques
C.I. Christodoulou;C.S. Pattichis;M. Pantziaris;A. Nicolaides.
IEEE Transactions on Medical Imaging (2003)
Comparative evaluation of despeckle filtering in ultrasound imaging of the carotid artery
C.P. Loizou;C.S. Pattichis;C.I. Christodoulou;R.S.H. Istepanian.
IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control (2005)
M-Health: Emerging Mobile Health Systems
Robert Istepanian;Swamy Laxminarayan;Constantinos S. Pattichis.
M-Health: Emerging Mobile Health Systems (2006)
What do we need to build explainable AI systems for the medical domain
Andreas Holzinger;Chris Biemann;Constantinos S. Pattichis;Douglas B. Kell.
arXiv: Artificial Intelligence (2017)
Unsupervised pattern recognition for the classification of EMG signals
C.I. Christodoulou;C.S. Pattichis.
IEEE Transactions on Biomedical Engineering (1999)
Snakes based segmentation of the common carotid artery intima media.
Christos P. Loizou;Constantinos S. Pattichis;Marios Pantziaris;T. Tyllis.
Medical & Biological Engineering & Computing (2007)
Multi-purpose HealthCare Telemedicine Systems with mobile communication link support
E Kyriacou;E Kyriacou;S Pavlopoulos;A Berler;M Neophytou.
Biomedical Engineering Online (2003)
Assessment of the Risk Factors of Coronary Heart Events Based on Data Mining With Decision Trees
Minas A Karaolis;Joseph A Moutiris;Demetra Hadjipanayi;Constantinos S Pattichis.
bioinformatics and bioengineering (2010)
Neural network models in EMG diagnosis
C.S. Pattichis;C.N. Schizas;L.T. Middleton.
IEEE Transactions on Biomedical Engineering (1995)
Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: