Abstract: Embodiments of the present invention described and shown in the specification and drawings include a system and method for monitoring the ventilation support provided by a ventilator that is supplying a breathing gas to a patient via a breathing circuit that is in fluid communication with the lungs of the patient.

Abstract: In general, the invention is directed to a technique for selection of parameter configurations for an implantable neurostimulator using Bayesian networks. The technique may be employed by a programming device to allow a clinician to select parameter configurations, including electrode configurations, and then program an implantable neurostimulator to deliver therapy using the selected parameter configurations. In operation, the programming device executes a parameter configuration search algorithm to guide the clinician in the selection of parameter configurations. The search algorithm relies on a Bayesian network structure that encodes conditional probabilities describing different states of the parameter set. The Bayesian network structure provides a conditional probability table that represents causal relationships between different parameter configurations.

Abstract: Embodiments of the present invention described and shown in the specification and drawings include a system and method for monitoring the ventilation support provided by a ventilator and automatically supplying a breathing gas to a patient via a breathing circuit that is in fluid communication with the lungs of the patient.

Abstract: A closed loop system uses (a) the intensity of the diaphragm electromyogram (EMG) for a given inspiratory volume; (b) the inspiratory volume for a given EMG intensity; or (c) a combination of (a) and (b); in view of controlling the level of gas flow, gas volume or gas pressure delivered by a mechanical (lung) ventilator. The closed loop ventilator system enables for automatic or manual adjustment of the level of inspiratory support in proportion to changes in the neuro-ventilatory efficiency such that the neural drive remains stable at a desired target level. An alarm can also be used to detect changes in neuroventilatory efficiency in view of performing manual adjustments.

Abstract: A method for extracting and evaluating features from cardiac acoustic signals includes the steps of obtaining a cardiac acoustic signal, extracting physiologically significant features from the cardiac acoustic signal using a neural network, analyzing the cardiac acoustic signal with a wavelist decomposition to extract time-frequency information, and identifying basic heart sounds using neutral networks applied to the extracted time-frequency information. A method for determining a status of heart murmurs includes the steps of obtaining a cardiac acoustic signal, detecting a murmur, if any, from the cardiac acoustic signal, and determining whether the murmur is one of functional and pathological based upon expert rules.

Abstract: Pulse oximetry is improved through classification of plethysmographic signals by processing the plethysmographic signals using a neural network that receives input coefficients from multiple signal domains including, for example, spectral, bispectral, cepstral and Wavelet filtered signal domains. In one embodiment, a plethysmographic signal obtained from a patient is transformed (240) from a first domain to a plurality of different signal domains (242, 243, 244, 245) to obtain a corresponding plurality of transformed plethysmographic signals. A plurality of sets of coefficients derived from the transformed plethysmographic signals are selected and directed to an input layer (251) of a neural network (250). The plethysmographic signal is classified by an output layer (253) of the neural network (250) that is connected to the input layer (251) by one or more hidden layers (252).

Abstract: A closed loop system uses (a) the intensity of the diaphragm electromyogram (EMG) for a given inspiratory volume; (b) the inspiratory volume for a given EMG intensity; or (c) a combination of (a) and (b); in view of controlling the level of gas flow, gas volume or gas pressure delivered by a mechanical (lung) ventilator. The closed loop ventilator system enables for automatic or manual adjustment of the level of inspiratory support in proportion to changes in the neuro-ventilatory efficiency such that the neural drive remains stable at a desired target level. An alarm can also be used to detect changes in neuroventilatory efficiency in view of performing manual adjustments.

Abstract: A method for generating time independent images of moving objects with the image information being related to properties of the moving objects represented by sequences of digital images. The images are transformed into a series of space-time representations of the image data. A function is derived from the space-time representation images that approximates the object motion and is used to create time independent images of the moving objects.

Abstract: A method for artifact reduction in sonomicrometer obtained intracranial pressure measurements generally comprises isolating a component of a sonomicrometer waveform attributable solely to changes in intracranial volume by using a neural network or other nonlinear engine to extract a heartbeat component from the sonomicrometer output. Because the heartbeat is so characteristic, no actual measurement of the heartbeat as the forcing function is required to isolate the resulting changes in distance from the artifact induced changes in distance. The neural network then be utilized to directly map measured changes in skull distance over time to changes in intracranial pressure over a volume change, the inverse of compliance. The method is generally extendable to use with other volumetric based measurement techniques.

Abstract: A system and method for providing computerized, knowledge-based medical diagnostic and treatment advice. The medical advice is provided to the general public over networks, such as a telephone network or a computer network. The invention also includes a stand-alone embodiment that may utilize occasional connectivity to a central computer by use of a network, such as the Internet. New authoring languages, interactive voice response and speech recognition are used to enable expert and general practitioner knowledge to be encoded for access by the public. “Meta” functions for time-density analysis of a number of factors regarding the number of medical complaints per unit of time are an integral part of the system. A re-enter feature monitors the user's changing condition over time. A symptom severity analysis helps to respond to the changing conditions. System sensitivity factors may be changed at a global level or other levels to adjust the system advice as necessary.

Abstract: A system and method for processing patient polysomnograph data are provided. An abstractor obtains raw patient polysomnograph data and generates a subset of the data to include selected factors, including data clusters. The subset of the patient polysomnograph data is transferred to two or more neural networks that process the data and generate sleep classification data. An integrator obtains the sleep classification data from the two or more neural networks by integrating the sleep classification data from each neural network. A cumulative sleep stage score is generated including confidence values and accuracy estimations for review.

Abstract: The present invention provides a system and method for monitoring the ventilation support provided by a ventilator that is supplying a breathing gas to a patient via a breathing circuit that is in fluid communication with the lungs of the patient. The ventilator has a plurality of selectable ventilator setting controls governing the supply of ventilation support from the ventilator, each setting control selectable to a level setting.

Abstract: A method and a system are provided for detection of seizures by applying advanced numerical analysis techniques to digitized waveforms of an electroencephalogram (EEG) recording. In an embodiment, the advanced numerical analysis techniques implemented in the method and system for detecting seizures include a combination of matching pursuit, neural network rules, and connected-object clustering algorithms.

Abstract: Diet evaluation gastric apparatus (18) is provided, which detects when a patient (10) swallows, and detects the type and amount of matter ingested. The apparatus includes electrodes (74, 100) adapted to be coupled to the fundus and antrum of the patient and to measure electrical and mechanical activity therein, and a control unit (90) to analyze such electrical and mechanical activity and optionally apply electrical energy to modify the activity of tissue of the patient.

Abstract: A method for gathering, organizing, and assessing patient information, then providing feedback to the patient and authorized caregivers. The patient provides health status and medication information to a processing center via an electronic communication network. The data may be encrypted before transmission for further protection. The patient's information is collected, organized, and stored in a data warehouse. Once collected, the patient information can be analyzed by a drug therapy analysis engine which reviews the patient's medications and health status in accordance with previously established medical practices and standards to determine whether the patient is receiving the optimum types and dosages of medication. Further, the drug therapy analysis engine can check for potential adverse side effects or drug interactions, given that patient's medical history and particular drug regimen. Security methods may be employed to prevent unauthorized parties from viewing or tampering with the data.

Abstract: A method and system improve the detection of abnormalities, such as lung nodules, in radiological images using digital image processing and artificial neural network techniques. The detection method and system use a nodule phantom for matching in order to enhance the efficiency in detection. The detection method and system use spherical parameters to characterize true nodules, thus enabling detection of the nodules in the mediastinum. The detection method and system use a multi-layer back-propagation neural network architecture not only for the classification of lung nodules but also for the integration of detection results from different classifiers. In addition, this method and system improve the detection efficiency by recommending the ranking of true nodules and several false positive nodules prior to the training of the neural network classifier. The method and system use image segmentation to remove regions outside the chest in order to reduce the false positives outside the chest region.

Abstract: To prevent erroneous detection of a ribcage boundary from a chest image, an outer search limit point is decided with precision. A profile of smoothed pixel-value integrated averages in each of right and left lung field of the image is obtained, a threshold for each of the right and left lung fields with the profile taken as a reference is decided, and each of the right and left lung fields is searched from a central part of each lung field outwardly on the image so that a position exceeding the threshold is determined. The position is set as the outer search limit point for a series of a upper lung ribcage boundary candidate points. In the search, in cases the position exceeding the threshold is not found, a first derivative of the profile is used to decide the outer search limit point.

Abstract: A method and a system are provided for detection of seizures by applying advanced numerical analysis techniques to digitized waveforms of an electroencephalogram (EEG) recording. In an embodiment, the advanced numerical analysis techniques implemented in the method and system for detecting seizures include a combination of matching pursuit, neural network rules, and connected-object clustering algorithms.

Abstract: A computer implemented system for the production of medical records, legal documents and other frequently produced semi-technical documents. This is accomplished by generating an intelligent computer-guided interview and the use of serialized scriptable objects. Major program elements include a knowledge base text file, a parse engine, and an execution module. The knowledge base uses a unique rule syntax. The parse engine converts the textual knowledge base file to a compiled binary representation which can then be interpreted by the execution module. The execution module leads the user through the interview by generating a series of questions and presents possible answers in the form of pick lists. The data is recorded with a computer pen and collated into a document file. This file is coded in binary format and can be written to and recalled from disk. If the file is recalled from disk the user can continue to answer questions or change answers previously given.

Abstract: A blood pressure Holter system includes a pneumatic constriction sleeve to be worn on an arm of the user and includes a first sensor for acquiring systolic and diastolic values of arterial pressure of the user. A second sensor is carried adjacent a chest of the user for sensing movement of the user's body. The system further includes a detection and classification circuit for detecting and classifying movement of the user's body for producing an index of a state of physical exertion corresponding to systolic and diastolic values of arterial pressure. A fuzzy logic controller processes the systolic and diastolic values of arterial pressure using fuzzy logic.

Abstract: A method of making a judgment on emotional positivist or negativity of a person, comprises the steps of obtaining asymmetry ratio between the brain waves of the left and right cerebral hemisphere measured in a given unit time by means of electrodes attached to the left and right side of the scalp, calculating asymmetry ratio versus time at each frequency of the measured brain waves if the time taken for measuring the brain waves exceeds a given time interval, calculating an increase and a decrease of the asymmetry ratio of the previous step with time, and entering the increase and decrease into an artificial neural network to make a judgment on the emotional positivity or negativity.

Abstract: Information derived from ECG signals and EEG signals may be employed in combination to reliably predict the onset, or to indicate the presence of, hypoglycemia in a human patient. In one embodiment, ECG and EEG signals are processed and the information derived from them is combined to determine whether a patient suffering from diabetes is undergoing a hypoglycemic event, or whether such an event is imminent. Input data from the patient or a health care provider may also be used to increase the accuracy and reliability of the system. Detection of a hypoglycemic event by the system can result in the output of an alarm signal and/or the delivery or administration of a beneficial agent such as insulin, glucagon or diazoxide to the patient. The system may be implantable, external, or a combination of external and implantable components. The control strategy of the present system is preferably microprocessor based and/or implemented using dedicated electronics.

Abstract: An electrode belt of a heart rate monitor, the electrode belt comprising one or more electrodes for measuring the heart rate on the chest, an electronics unit for handling the information to be received from the electrode, a conductor for providing electrical contact between the electronics unit and the electrode, at least one wavelike supporting structure provided with alternating upwards and downwards directing sections and intended for protecting the conductor. The conductor of the electrode belt follows the shape of the supporting structure, thus having a wavelike form.

Abstract: A heart rate measurement arrangement wherein the heart rate measurement arrangement comprises a calculating unit comprising a mathematical model arranged to form a person's energy metabolism level as an output parameter of the model using as input parameters of the model one or more heart rate parameters and one or more physiological parameters each describing a physiological characteristic of the person, the heart rate measurement arrangement further comprising display means for displaying information formed in the calculating unit.

Abstract: Structure-based processing includes a method of diagnosing diseases that works by arranging diseases, symptoms, and questions into a set of related disease, symptom, and question structures, such as objects or lists, in such a way that the structures can be processed to generate a dialogue with a patient. A structure-based processing system organizes medical knowledge into formal structures and then executes those structures on a structure engine to automatically select the next question. Patient responses to the questions lead to more questions and ultimately to a diagnosis. An object-oriented embodiment includes software objects utilized as active, intelligent agents where each object performs its own tasks and calls upon other objects to perform their tasks at the appropriate time to arrive at a diagnosis.

Abstract: Structure-based processing includes a method of diagnosing diseases that works by arranging diseases, symptoms, and questions into a set of related disease, symptom, and question structures, such as objects or lists, in such a way that the structures can be processed to generate a dialogue with a patient. A structure-based processing system organizes medical knowledge into formal structures and then executes those structures on a structure engine to automatically select the next question. Patient responses to the questions lead to more questions and ultimately to a diagnosis. An object-oriented embodiment includes software objects utilized as active, intelligent agents where each object performs its own tasks and calls upon other objects to perform their tasks at the appropriate time to arrive at a diagnosis.

Abstract: A method of producing a control signal. The method includes the steps of sensing an air pressure pattern in or near an ear of a person, the air pressure pattern resulting from voluntary physical action of the person; and converting the air pressure pattern into an output signal. Also described is a control system. The control system includes an air pressure sensor for detecting an air pressure pattern adjacent an ear of a person while the person makes a voluntary physical action and for producing an output signal corresponding to the detected air pressure pattern; and processing circuitry for discerning a pattern from the output signal.

Abstract: Structure-based processing includes a method of diagnosing diseases that works by arranging diseases, symptoms, and questions into a set of related disease, symptom, and question structures, such as objects or lists, in such a way that the structures can be processed to generate a dialogue with a patient. A structure-based processing system organizes medical knowledge into formal structures and then executes those structures on a structure engine to automatically select the next question. Patient responses to the questions lead to more questions and ultimately to a diagnosis. An object-oriented embodiment includes software objects utilized as active, intelligent agents where each object performs its own tasks and calls upon other objects to perform their tasks at the appropriate time to arrive at a diagnosis.

Abstract: Structure-based processing includes a method of diagnosing diseases that works by arranging diseases, symptoms, and questions into a set of related disease, symptom, and question structures, such as objects or lists, in such a way that the structures can be processed to generate a dialogue with a patient. A structure-based processing system organizes medical knowledge into formal structures and then executes those structures on a structure engine to automatically select the next question. Patient responses to the questions lead to more questions and ultimately to a diagnosis. An object-oriented embodiment includes software objects utilized as active, intelligent agents where each object performs its own tasks and calls upon other objects to perform their tasks at the appropriate time to arrive at a diagnosis.

Abstract: A randomization mechanism for enabling randomization of a patient to one of two treatment options having different time-to-treatments is presented. Data is received for a patient experiencing symptoms of the type treatable by either of the two treatment options. The received data is used to compute for a first treatment option of the two treatment options at its associated time-to-treatment a benefit value. Assuming a benefit value for the second treatment option is an estimate of the computed first benefit value, the received data and computed benefit value are used to compute a maximum allowable delay time during which the benefit value for the second treatment option is no less than the benefit value computed for the first treatment option. When provided a given delay time by which the time-to-treatment of the second treatment option lags the first treatment option time-to-treatment, the mechanism determines if the given delay time is less than or equal to the allowable delay time.

Abstract: The present invention provides methods and apparatuses, which make use of at least one trained and tuned artificial neural network (16) to generate decision regions (32) in the n-dimensional space of n input variables associated with AMI. The set of measured variables (30) is related to the decision regions (32), in order to provide decision support. Preferably, the decision regions (32) are graphically visualized as areas in a two-dimensional diagram. Preferably, the artificial neural network (16) is trained by patient specific parameters. The variables associated with AMI (30) are preferably selected as biochemical markers and/or quantities derived from continuous/intermittent ECG/VCG. The performance of the artificial neural network (16) is preferably optimally tuned to clinical requirements on predictive values of the artificial neural network output in given prevalence situations.

Abstract: A method for remotely monitoring and identifying Functional Activities performed by a test subject, the method including the steps of (a) extracting a given type of signals from each of a predetermined set of muscles of a control subject during the performance thereby of a given Functional Activity; (b) processing the signals to provide therefor given parameters affected by the given Functional Activity; (c) storing the data obtained in step (b); and (d) repeating steps (a)-(c) for a plurality of other control subjects. The stored data then is utilized to establish a normative data base indicative of the given Functional Activity and further steps include (f) extracting the given type of signals from each of at least some of the predetermined set of muscles of a test subject during a given monitoring period; and (g) comparing the data base to the signals of step (f) to identify during the monitoring period portions thereof during which the test subject was performing the given Functional Activity.

Abstract: A remote maintenance and operating guidance system in which data relating to the operation of a medical system in a hospital is transmitted to an operator who operates an operating device of the medical system from a service center by way of a communication device such as a dedicated telephone line. The system is equipped to monitor operations performed by the operator on the medical system, and to transmit data relating to the monitored operation to the operating device.

Abstract: An automated method and/or system for identifying suspected lesions in a brain is provided. A processor (a) provides a magnetic resonance image (MRI) of a patient's head, including a plurality of slices of the patient's head, which MRI comprises a multispectral data set that can be displayed as an image of varying pixel intensities. The processor (b) identifies a brain area within each slice to provide a plurality of masked images of intracranial tissue. The processor (c) applies a segmentation technique to at least one of the masked images to classify the varying pixel intensities into separate groupings, which potentially correspond to different tissue types. The processor (d) refines the initial segmentation into the separate groupings of at least the first masked image obtained from step (c) using one or more knowledge rules that combine pixel intensities with spatial relationships of anatomical structures to locate one or more anatomical regions of the brain.

Abstract: A hands-free human-machine interface uses body position, limb motion, speech signals, and/or changes in the operator's level of cognition and/or stress to control the user interface of an interactive system. Signals are acquired from mental and/or physical processes, such as brainwaves, eye, heart, and muscle activities, larynx activity, body position and motion changes, and stress indicating measures. The signals are measured and processed to replace a hand-operated mouse, keypad, joystick, video game, or other controls with a motion-based gestural interface that works, optionally in conjunction with a larynx activated speech processor. For disabled individuals without sufficient dexterity and speech capacity, multimodal neuroanalysis will reveal intended movements and these will be used to operate an imagined mouse or keypad.

Abstract: The present invention relates to a method and apparatus for the construction and/or use of multidimensional fields that can be used for high-resolution detection and characterization of features within objects. The multidimensional field is constructed from data that is collected by an array of radiation detectors that substantially surround the object under study. The detected radiation is produced by an array of radiation sources and is subsequently scattered, reflected, transmitted, or diffracted by the object under study and any features within the object under study. In particular embodiments of the invention, the radiation that is used is ultrasonic radiation and the object under study is human or animal tissue or an organ. In this case, the invention permits the detection and identification of cancer by an intelligently trained evaluation system.

Abstract: Disclosed is a system and method for determining a severity of a stenosis in a blood vessel depicted in a magnetic resonance imaging (MRI) data set. The system comprises a neural network configured to calculate the severity of the stenosis in the blood vessel based upon a number of input parameters, and the input parameters including at least one characteristic of a signal void associated with the stenosis in the MRI data set. The input parameters may include, for example, a flow rate of blood through the blood vessel, a length of a longitudinal axis of the signal void, and an average image intensity along the longitudinal axis of the signal void as well as other input parameters.

Abstract: In accordance with the apparatus and method of the present invention, a biopotential lesion sensor is placed directly over a lesion in a symptomatic breast and a reference sensor is located away from the symptomatic breast. A plurality of electropotential test measurements are taken during a test period with the lesion sensor and averaged to obtain a primary test potential. This primary test potential can be weighted to compensate for one or more biologic variables such as patient age, time in the patient menstrual cycle, and the time of day during which the measurement is taken. To provide noise enhancement of the primary test potential average measurement, the symptomatic breast is divided into four equal quadrants with one quadrant containing the lesion.

Abstract: Structure-based processing includes a method of diagnosing diseases that works by arranging diseases, symptoms, and questions into a set of related disease, symptom, and question structures, such as objects or lists, in such a way that the structures can be processed to generate a dialogue with a patient. A structure-based processing system organizes medical knowledge into formal structures and then executes those structures on a structure engine to automatically select the next question. Patient responses to the questions lead to more questions and ultimately to a diagnosis. An object-oriented embodiment includes software objects utilized as active, intelligent agents where each object performs its own tasks and calls upon other objects to perform their tasks at the appropriate time to arrive at a diagnosis.

Abstract: A blood pressure Holter system includes a pneumatic constriction sleeve to be worn on an arm of the user and includes a first sensor for acquiring systolic and diastolic values of arterial pressure of the user. A second sensor is carried adjacent a chest of the user for sensing movement of the user's body. The system further includes a detection and classification circuit for detecting and classifying movement of the user's body for producing an index of a state of physical exertion corresponding to systolic and diastolic values of arterial pressure. A fuzzy logic controller processes the systolic and diastolic values of arterial pressure using fuzzy logic.

Abstract: A heart rate measurement arrangement wherein the heart rate measurement arrangement comprises a calculating unit comprising a mathematical model arranged to form a person's energy metabolism level as an output parameter of the model using as input parameters of the model one or more heart rate parameters and one or more physiological parameters each describing a physiological characteristic of the person, the heart rate measurement arrangement further comprising display means for displaying information formed in the calculating unit.

Abstract: The present invention relates to a method and an apparatus for measuring exercise condition, especially a method for measuring an exertion endurance indicator representing exercise condition of a subject to be measured, such as maximal oxygen uptake or any such exertion endurance indicator representing exercise condition. The method is characterized in that, in the method a predetermined calculation formula is used preferably by means of a neural network, to which formula physiological parameters representing the subject to be measured are supplied. The input parameters comprise at least one or more of the following physiological parameters, such as sex, age, height, weight. One or more output parameters representing the exertion endurance indicator representing the exercise condition of the subject to be measured are obtained as a result from the calculation formula.

Abstract: A system for automated detection of cancerous masses in mammograms initially identifies regions of interest (ROIs) using Fourier analysis (e.g., by means of an optical correlator). Context data is extracted from the mammogram for each ROI, such as size, location, ranking, brightness, density, and relative isolation from other ROIs. The pixels in the ROI are averaged together to create a smaller array of super-pixels, which are input into a first neural net. A second neural net receives the output values from the first neural net and the context data as inputs and generates an output score indicating whether the ROI contains a cancerous mass. The second neural net can also be provided with context data from another view of the same breast, the same view of the other breast, or a previous mammogram for the same patient.

Abstract: An apparatus for iteratively estimating an intra-arterial blood-pressure value of a living subject, including a first information obtaining device which non-invasively and iteratively obtains information relating to propagation of a pulse wave through an arterial vessel of the subject, a second information obtaining device which non-invasively and iteratively obtains information relating to heartbeat of the subject and/or information relating to area of a heartbeat-synchronous pulse of a volumetric pulse wave obtained from a peripheral body portion of the subject, and an estimating device including a neural network which learns sets of information each set of which includes a blood-pressure value measured using a cuff, pulse-wave-propagation-relating information obtained when the blood-pressure value is measured using the cuff, and heartbeat-relating information and/or pulse-wave-area-relating information obtained when the blood-pressure value is measured using the cuff, the neural network iteratively estimat

Abstract: A new method to analyze and predict the binding energy for enzyme-transition state inhibitor interactions is presented. Computational neural networks are employed to discovery quantum mechanical features of transition states and putative inhibitors necessary for binding. The method is able to generate its own relationship between the quantum mechanical structure of the inhibitor and the strength of binding. Feed-forward neural networks with back propagation of error can be trained to recognize the quantum mechanical electrostatic potential at the entire van der Waals surface, rather than a collapsed representation, of a group of training inhibitors and to predict the strength of interactions between the enzyme and a group of novel inhibitors. The experimental results show that the neural networks can predict with quantitative accuracy the binding strength of new inhibitors.

Abstract: A computer-aided diagnosis (CAD) method for the automated detection of lung nodules in a digital chest image, a computer programmed to implement the method, and a storage medium which stores a program for implementing the method, wherein nodule candidates are first automatically selected by thresholding the difference image and then classified in six groups. A large number of false positives are eliminated by adaptive rule-based tests applied to the original chest image and in the difference image and an artificial neural network (ANN) applied to remaining candidate nodule locations in the original chest image. Using two hundred PA chest radiographs, 100 normal and 100 abnormal, as the database, the presence of nodules in the 100 abnormal cases was confirmed by two experienced radiologists on the basis of CT scans or radiographic follow-up. The CAD method achieves, on average, the sensitivity of 70% at 1.7 false positives per chest image.

Abstract: An apparatus and methods for spectroscopic detection of tissue abnormality, particularly precancerous cervical tissue, using neural networks to analyze in vivo measurements of fluorescence spectra. The invention excites fluorescence intensity spectra in both normal and abnormal tissue. This fluorescence spectroscopy data is used to train a group (ensemble) of neural networks, preferably radial basis function (RBF) neural networks. Once trained, fluorescence spectroscopy data from unknown tissue samples is classified by the trained neural networks. This process is used to differentiate pre-cancers from normal tissues, and can also be used to differentiate high grade pre-cancers from low grade pre-cancers. One embodiment of the invention is able to distinguish pre-cancerous tissue from both normal squamous tissue (NS) and normal columnar (NC) tissue in a single-stage of analysis.

Abstract: Apparatus and method for non-invasive diagnosis of cardiovascular and related disorders. The system establishes a correspondence between the dynamics of the wave contour of the arterial pressure pulse and the associated disease states. The system comprises an input module, a contour signal receiver, and a processing module. The input module utilizes a pressure transducer for taking a non-invasive measurement of the arterial pulse. The contour signal receiver amplifies, digitizes and normalizes the arterial pressure pulse signal. In the processing module, the normalized arterial pressure contour is subjected to wavelet analysis, which transforms the dynamics of the time series of arterial blood pressure contour into multi-resolution wavelet coefficients or signatures. The processing module includes a neural network which is trained to associate the diagnostic features of the transformed arterial pressure contour embedded in the coefficients with a disease condition.

Abstract: A system and method for providing computerized, knowledge-based medical diagnostic and treatment advice. The medical advice is provided to the general public over a telephone network. Two new authoring languages, interactive voice response and speech recognition are used to enable expert and general practitioner knowledge to be encoded for access by the public. "Metal" functions for time-density analysis of a number of factors regarding the number of medical complaints per unit of time are an integral part of the system. A semantic discrepancy evaluator routine along with a mental status examination are used to detect the consciousness level of a user of the system. A re-enter feature monitors the user's changing condition over time. A symptom severity analysis helps to respond to the changing conditions. System sensitivity factors may be changed at a global level or other levels to adjust the system advice as necessary.

Abstract: A computerized imaging system (such as CAT scan, MRI imaging, ultrasound imaging, infrared, X-ray, UV/visible light fluorescence, Raman spectroscopy or microwave imaging) is employed to sense the position of an endoscopic treatment system within the body of a patient. In a preferred embodiment, the system provides real-time computer control to maintain and adjust the position of the treatment system and/or the position of the patient relative to the treatment system; and also provides (if desired) real-time computer control of the operation of the treatment system itself. Other embodiments include scanning mechanisms for directing laser light or other radiation under controlled conditions at select locations within the body.