Patient management in CCUs: Need for an intelligent interpretation of signals

[1]  N. Fowler,et al.  Unreliability of conventional electrocardiography monitoring for arrhythmia detection in coronary care units , 1973 .

[2]  Blackford Middleton,et al.  Building a speech interface to a medical diagnostic system , 1991, IEEE Expert.

[3]  Senén Barro,et al.  Knowledge-Based Fuzzy Classification of Signal Events , 1991, MIE.

[4]  Evangelos E. Milios,et al.  Signal abstractions in signal processing software , 1989, IEEE Trans. Acoust. Speech Signal Process..

[5]  M S Golden,et al.  Prevalence of total coronary occlusion during the early hours of transmural myocardial infarction. , 1980, The New England journal of medicine.

[6]  E. Braunwald,et al.  Myocardial reperfusion, limitation of infarct size, reduction of left ventricular dysfunction, and improved survival. Should the paradigm be expanded? , 1989, Circulation.

[7]  S. Barro,et al.  Systolic Implementation of DBT-Transformed Fuzzy Control Systems , 1992 .

[8]  A. Bugarin,et al.  Strategies For Intelligent Signal Monitoring , 1991, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society Volume 13: 1991.

[9]  S Barro,et al.  Fuzzy beat labeling for intelligent arrhythmia monitoring. , 1990, Computers and biomedical research, an international journal.

[10]  J. A. Blom.  SIMPLEXYS Real Time Expert Systems in Patient Monitoring , 1991 .

[11]  B.H. Jansen,et al.  Knowledge-based interpretation of bioelectrical signals , 1990, IEEE Engineering in Medicine and Biology Magazine.

[12]  Perry L. Miller,et al.  Real-time data fusion in the intensive care unit , 1991, Computer.

[13]  A. I. Cohn.  Automated Patient-specific Data Interpretation In An Intelligent Cardiovascular Monitor , 1991, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society Volume 13: 1991.

[14]  H.-J. Zimmermann,et al.  A knowledge-based approach to intelligent alarms in anesthesia , 1991, IEEE Engineering in Medicine and Biology Magazine.

[15]  S Barro,et al.  Grammatic representation of beat sequences for fuzzy arrhythmia diagnosis. , 1991, International journal of bio-medical computing.

[16]  D. Harrington.  Medical device networks. , 1990, Journal of clinical engineering.

[17]  P L Miller,et al.  DYNASCENE: an approach to computer-based intelligent cardiovascular monitoring using sequential clinical "scenes". , 1990, Methods of information in medicine.

[18]  S. Furuie,et al.  Safety in medical signal analysis , 1991, IEEE Engineering in Medicine and Biology Magazine.

[19]  Lawrence M. Fagan.  VM, representing time-dependent relations in a medical setting , 1980 .

[20]  C Michelassi,et al.  Unreliability of conventional visual electrocardiographic monitoring for detection of transient ST segment changes in a coronary care unit. , 1984, European heart journal.

[21]  Janos Sztipanovits,et al.  Model based approach in intelligent patient monitoring , 1988, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[22]  P. Ouyang,et al.  Frequency and importance of silent myocardial ischemia identified with ambulatory electrocardiographic monitoring in the early in-hospital period after acute myocardial infarction. , 1990, The American journal of cardiology.

[23]  Giovanni Bortolan,et al.  Fuzzy decision-making in electrocardiography , 1989, Artif. Intell. Medicine.

[24]  O Wigertz,et al.  Evaluation of decision support systems in medicine. , 1991, Computer methods and programs in biomedicine.

[25]  P. Cohn.  Silent Myocardial Ischemia and Infarction , 1986 .

[26]  Peter C. Dibble,et al.  Os-9 Insights: An Advanced Programmers Guide to Os-9 , 1988 .

[27]  D. G. Cramp,et al.  AIRS — An Artificial Intelligent Respirator System , 1988 .

[28]  G. Vetrovec.  Changing concepts in the pathophysiology of myocardial ischemia. , 1989, The American journal of cardiology.