Development of Physics Applied to Medicine in the UK, 1945–90

Annotated and edited transcript of a Witness Seminar held on 5 July 2005. Introduction by Dr Jeff Hughes.First published by the Wellcome Trust Centre for the History of Medicine at UCL, 2006.©The Trustee of the Wellcome Trust, London, 2006.All volumes are freely available online at: www.history.qmul.ac.uk/research/modbiomed/wellcome_witnesses/Annotated and edited transcript of a Witness Seminar held on 5 July 2005. Introduction by Dr Jeff Hughes.Annotated and edited transcript of a Witness Seminar held on 5 July 2005. Introduction by Dr Jeff Hughes.Annotated and edited transcript of a Witness Seminar held on 5 July 2005. Introduction by Dr Jeff Hughes.Annotated and edited transcript of a Witness Seminar held on 5 July 2005. Introduction by Dr Jeff Hughes.Annotated and edited transcript of a Witness Seminar held on 5 July 2005. Introduction by Dr Jeff Hughes.Annotated and edited transcript of a Witness Seminar held on 5 July 2005. Introduction by Dr Jeff Hughes.Organized with the assistance of Professor John Clifton (UCL) and chaired by Professor Peter Williams (Manchester), this seminar examined the early developments of medical physics in the UK between 1945 and 1990. Participants discussed a range of themes including medical physics before and during the war, the role of the King's Fund and the formation of the Hospital Physicists' Association (HPA), expansion of medical physics outside radiotherapy and to non-radiation physics (ultrasound, medical instrumentation, bioengineering, use of digital computers), developing regional services and links with industry. The seminar finished with a discussion on the changing scene in the 1980s, covering topics such as funding, academic and undergraduate medical physics, imaging, CT, NMR and others. Participants included Mr Tom Ashton, Dr Barry Barber, Professors Roland Blackwell and Terence Burlin, Dr Joseph Blau, Mr Bob (John) Burns, Professors John Clifton, David Delpy, Philip Dendy and Jack Fowler, Dr Jean Guy, Mr John Haggith, Drs John Haybittle, Alan Jennings and John Law, Professors John Mallard and Joe McKie, Mr David Murnaghan, Professor Angela Newing, Dr Sydney Osborn, Professor Rodney Smallwood, Dr Adrian Thomas, Dr Peter Tothill, Mr Theodore Tulley, Professors Peter Wells and John West, and Mr John Wilkinson. Christie D A, Tansey E M. (eds) (2006) Development of physics applied to medicine in the UK, 1945–90, Wellcome Witnesses to Twentieth Century Medicine, vol. 28. London: The Wellcome Trust Centre for the History of Medicine at UCL.The Wellcome Trust Centre for the History of Medicine at UCL is funded by the Wellcome Trust, which is a registered charity, no. 210183

Łukasiewicz-Moisil Many-Valued Logic Algebra of Highly-Complex Systems

A novel approach to self-organizing, highly-complex systems (HCS), such as living organisms and artificial intelligent systems (AIs), is presented which is relevant to Cognition, Medical Bioinformatics and Computational Neuroscience. Quantum Automata (QAs) were defined in our previous work as generalized, probabilistic automata with quantum state spaces (Baianu, 1971). Their next-state functions operate through transitions between quantum states defined by the quantum equations of motion in the Schroedinger representation, with both initial and boundary conditions in space-time. Such quantum automata operate with a quantum logic, or Q-logic, significantly different from either Boolean or Łukasiewicz many-valued logic. A new theorem is proposed which states that the category of quantum automata and automata--homomorphisms has both limits and colimits. Therefore, both categories of quantum automata and classical automata (sequential machines) are bicomplete. A second new theorem establishes that the standard automata category is a subcategory of the quantum automata category. The quantum automata category has a faithful representation in the category of Generalized (M,R)--Systems which are open, dynamic biosystem networks with defined biological relations that represent physiological functions of primordial organisms, single cells and higher organisms

Early Diagnosis of Alzheimer's disease by NIRF Spectroscopy and Nuclear Medicine

There is an urgent need for the early detection of diseases such as Alzheimer’s (AD) and Cancers in order to enable their successful treatment. Cancer is the second major cause of death after Heart Disease, and AD is the third major cause of death with major, human and financial/economics trillion dollar consequences for the society. Nuclear Medicine is concerned with applications in Medicine of Nuclear Science and Engineering techniques and knowledge. Three major Nuclear Medicine techniques that are established for diagnostic and research purposes are: Positron Emission Tomography (PET) and CAT/CT, Nuclear Magnetic Resonance Imaging (NMRI/MRI). However, these three techniques have also major limitations in terms of either cost or image resolution, as well as patient irradiation in the case of CAT/CT and PET. On the other hand, Near Infrared Chemical Imaging Microspectroscopy and certain Fluorescence spectroscopic techniques are capable of single cancer cell and/or single molecule detection and/or imaging. Such powerful capabilities, combined with low cost of diagnostics, make these novel techniques very attractive means for early detection of diseases such as cancer and Alzheimer’s, that are promising to reduce the fatality rate of patients through adequate diagnosis and treatment of such diseases at early stages. 
Currently NIH provides only inadequate funding for the clinical and research aspects of these novel investigation and clinical diagnostic techniques by FT-NIRS and Fluorescence spectrocopy for early detection of Alzheimer's and Cancers

User-centered visual analysis using a hybrid reasoning architecture for intensive care units

One problem pertaining to Intensive Care Unit information systems is that, in some cases, a very dense display of data can result. To ensure the overview and readability of the increasing volumes of data, some special features are required (e.g., data prioritization, clustering, and selection mechanisms) with the application of analytical methods (e.g., temporal data abstraction, principal component analysis, and detection of events). This paper addresses the problem of improving the integration of the visual and analytical methods applied to medical monitoring systems. We present a knowledge- and machine learning-based approach to support the knowledge discovery process with appropriate analytical and visual methods. Its potential benefit to the development of user interfaces for intelligent monitors that can assist with the detection and explanation of new, potentially threatening medical events. The proposed hybrid reasoning architecture provides an interactive graphical user interface to adjust the parameters of the analytical methods based on the users' task at hand. The action sequences performed on the graphical user interface by the user are consolidated in a dynamic knowledge base with specific hybrid reasoning that integrates symbolic and connectionist approaches. These sequences of expert knowledge acquisition can be very efficient for making easier knowledge emergence during a similar experience and positively impact the monitoring of critical situations. The provided graphical user interface incorporating a user-centered visual analysis is exploited to facilitate the natural and effective representation of clinical information for patient care