Analog Computer-Aided Detection (CAD) information can be more effective than binary marks.

In socially important visual search tasks, such as baggage screening and diagnostic radiology, experts miss more targets than is desirable. Computer-aided detection (CAD) programs have been developed specifically to improve performance in these professional search tasks. For example, in breast cancer screening, many CAD systems are capable of detecting approximately 90% of breast cancer, with approximately 0.5 false-positive detections per image. Nevertheless, benefits of CAD in clinical settings tend to be small (Birdwell, 2009) or even absent (Meziane et al., 2011; Philpotts, 2009). The marks made by a CAD system can be "binary," giving the same signal to any location where the signal is above some threshold. Alternatively, a CAD system presents an analog signal that reflects strength of the signal at a location. In the experiments reported, we compare analog and binary CAD presentations using nonexpert observers and artificial stimuli defined by two noisy signals: a visible color signal and an "invisible" signal that informed our simulated CAD system. We found that analog CAD generally yielded better overall performance than binary CAD. The analog benefit is similar at high and low target prevalence. Our data suggest that the form of the CAD signal can directly influence performance. Analog CAD may allow the computer to be more helpful to the searcher.

Scalable closed-boundary analog neural networks.

In many pattern-classification and recognition problems, separation of different swarms of class representatives is necessary. As well, in function-approximation problems, neurons with a local area of influence have demonstrated measurable success. In our previous work, we have shown how intrinsic quadratic characteristics of traditional metal-oxide-semiconductor (MOS) devices can be used to implement hyperspherical discriminating surfaces in hardware-implemented neurons. In this work, we further extend the concept from quadratic forms to more-arbitrary closed-boundary shapes. Accordingly, we demonstrate how intrinsic characteristics of submicron MOS devices can be utilized to implement efficient pattern discriminators for various applications and, through representative simulations, show their success in some typical function-approximation problems. Further, we offer two mathematical interpretations of possible roles for these networks: Geometrically, we show that our networks employ closed hypercone shapes as their discriminating surfaces; analytically, we show that a set of these synapses connected to a common integrating body calculates the distance between their inputs and weight vectors using a power norm. The feasibility of the idea is practically investigated by design, implementation, and test of a three-dimensional (3-D) closed-boundary pattern classifier, fabricated in 0.35-microm complimentary MOS, whose results are reflected in this work.

The application of cross-point switch arrays as input selector switch devices for multi-channel electrophysiological experiments.

Integrated circuits (ICs) containing cross-point switch arrays were applied to create analog input selector switch devices for multi-channel electrophysiological experiments. The described analog input selector switch devices make it possible to connect to the main amplifier's inputs those microelectrode and preamplifier output wires that yield unit discharges of acceptable shape and amplitude, or yield other kind of acceptable electrophysiological signals (EEG, EP). This kind of selector allows to use higher number of preamplifier channels and to ignore the input channels without adequate signals or the channels with noisy inputs. No manual switching is required, as the work is done by computer controlled switches. The switch positions can be saved and reloaded at the next experimental session through an I/O port (e.g. the parallel port) of the computer.

International standard (C.C.I.T.T.) for transmitting biomedical analogue and digital data on the public telephone network.

Analogue transmission of biomedical signals over the public telephone network has advantages from the economic point of view over digitalized transmission. This paper deals with the special problems encountered with the transmission of biomedical signals. Furthermore, the new international transmission standard C.C.I.T.T. recommendation V. 16 is introduced. This standard has recently been adopted by the relevant study group and has been presented to the Plenary Assembly of the C.C.I.T.T. for final approval. This standard is compatible with the existing public telephone networks. The technical specifications of this standard allow the transmission of the three-channel ECG for diagnostic purposes, e.g., remote processing and computer-assisted evaluation, as well as the transmission of the one-channel ECG with acoustic coupling, e.g., in emergency cases and for pace maker monitoring.

The precision of a special purpose analog computer in clinical cardiac output determination.

Three hundred dye-dilution curves taken during our first year of clinical experience with the Waters CO-4 cardiac output computer were analyzed to estimate the errors involved in its use. Provided that calibration is accurate and 5.0 mg of dye are injected for each curve, then the percentage standard deviation of measurement using this computer is about 8.7%. Included in this are the errors inherent in the computer, errors due to baseline drift, errors in the injection of dye and acutal variation of cardiac output over a series of successive determinations. The size of this error is comparable to that involved in manual calculation. The mean value of five successive curves will be within 10% of the real value in 99 cases out of 100. Advances in methodology and equipment are discussed which make calibration simpler and more accurate, and which should also improve the quality of computer determination. A list of suggestions is given to minimize the errors involved in the clinical use of this equipment.