Abstract: Methods and systems for selecting a cohort group or a patient at risk from a population of patients with mild cognitive impairment. The methods include using a computer configured to perform the steps: receiving normalized learning data from a portion of the population of patients; tuning a set of decision trees on the normalized learning data; receiving patient data from one or more patients of the population, wherein the patient data is independent from the learning data; classifying the patient data with the tuned set of decision trees to obtain patient threshold values; and displaying the patient threshold values.

Abstract: An electronic clinical decision support system (CDSS) (10, 12) comprises: an inference engine (20, 22) configured to generate clinical decision recommendations for a patient based on information pertaining to the patient, the inference engine comprising rules (16) developed by a plurality of medical experts (14) and codified into software; an electronic outliers detector (52) configured to detect outlier cases that are probative of a potential flaw in the inference engine; an outliers database (60) configured to collect information pertaining to the outlier cases detected by the electronic outliers detector; and an outliers report generator (62) configured to generate a report (64) on the outlier cases detected by the electronic outliers detector, the generated report containing at least some information collected in the outliers database.

Abstract: Methods and systems for selecting a cohort group or a patient at risk from a population of patients with mild cognitive impairment. The methods include using a computer configured to perform the steps: receiving normalized learning data from a portion of the population of patients; tuning a set of decision trees on the normalized learning data; receiving patient data from one or more patients of the population, wherein the patient data is independent from the learning data; classifying the patient data with the tuned set of decision trees to obtain patient threshold values; and displaying the patient threshold values.

Abstract: A medical apparatus (901, 100) assists clinicians, nurses or other users in choosing an intervention for the treatment of a patent suffering from an acute dynamic disease, e.g. sepsis. The medical apparatus is based on a method where a model of the disease is adapted or personalized to the patient. To ensure that the apparatus remains capable of predicting the health of the patient, the apparatus is continuously provided with new, more recent patient values and the model is continuously adapted to the new patient values. Since the medical apparatus is configured to be continuously adapted to current state of health, the apparatus is able to assist the user by generating disease management information, e.g. suggestions for medications, to an output device (902, 104).

Abstract: A method for determining the presence or absence of malignant features in medical images, wherein a plurality of base comparison or training images of various types of lesions taken of actual patient is examined by one or more image reading experts to create a first database array. Low-level features of each of the lesions in the same plurality of base comparisons or training images are determined using one or more image processing algorithms to obtain a second database array set. The first and second database array set are combined to create a training database array set which is input to a learning system that discovers/learns a classifier that maps from a subset of the low-level features to the expert's evaluation in the first database array set. The classifier is used to determine the presence of a particular mid-level feature in an image of lesion in a patient based solely on the image.

Abstract: A method of automatically identifying the microarray chip corners and probes, even if there are no probes at the corners, in a high density and high resolution microarray scanned image having an image space, wherein the method minimizes the error distortions in the image arising in the scanning process by applying to the image a multipass corner finding algorithm comprising: (a) applying a Radon transform to an input microarray image to project the image into an angle and distance space where it is possible to find the orientation of the straight lines; (b) applying a fast Fourier transform to the projected image of (a) to find the optimal tilting angle of the projected image; (c) determining the optimal first and last local maxima for the optimal tilting angle; (d) back projecting the determined first and last local maxima to the image space to find the first approximation of the first and last column lines of the image; (e) rotating the image and repeating steps (a) through (d) to find the first approximati

Abstract: A pre-examination patient information gathering system comprises an electronic user interface (30, 130) including a display (32) and at least one user input device (34, 36), and an electronic processor (50) configured to present an initial set of questions (54) to a patient via the electronic user interface, receive responses to the initial set of questions from the patient via the electronic user interface, construct or select follow-up questions (68) based on the received responses, present the constructed or selected follow up questions to the patient via the electronic user interface, and receive responses to the constructed or selected follow up questions from the patient via the electronic user interface. A physiological sensor (70, 72, 74, 76, 78, 80) may be configured to autonomously sense a patient physiological parameter as the patient interacts with the electronic user interface.

Abstract: An electronic clinical decision support system (CDSS) (10, 12) comprises: an inference engine (20, 22) configured to generate clinical decision recommendations for a patient based on information pertaining to the patient, the inference engine comprising rules (16) developed by a plurality of medical experts (14) and codified into software; an electronic outliers detector (52) configured to detect outlier cases that are probative of a potential flaw in the inference engine; an outliers database (60) configured to collect information pertaining to the outlier cases detected by the electronic outliers detector; and an outliers report generator (62) configured to generate a report (64) on the outlier cases detected by the electronic outliers detector, the generated report containing at least some information collected in the outliers database.

Abstract: A method of automatically identifying the microarray chip corners and probes, even if there are no probes at the corners, in a high density and high resolution microarray scanned image having an image space, wherein the method minimizes the error distortions in the image arising in the scanning process by applying to the image a multipass corner finding algorithm comprising: (a) applying a Radon transform to an input microarray image to project the image into an angle and distance space where it is possible to find the orientation of the straight lines; (b) applying a fast Fourier transform to the projected image of (a) to find the optimal tilting angle of the projected image; (c) determining the optimal first and last local maxima for the optimal tilting angle; (d) back projecting the determined first and last local maxima to the image space to find the first approximation of the first and last column lines of the image; (e) rotating the image and repeating steps (a) through (d) to find the first approximati

Abstract: A method for determining the presence or absence of malignant features in medical images, wherein a plurality of base comparison or training images of various types of lesions taken of actual patient is examined by one or more image reading experts to create a first database array. Low-level features of each of the lesions in the same plurality of base comparisons or training images arc determined using one or more image processing algorithms to obtain a second database array set. The first and second database array set are combined to create a training database array set which is input to a learning system that discovers/learns a classifier that maps from a subset of the low-level features to the expert's evaluation in the first database array set. The classifier is used to determine the presence of a particular mid-level feature in an image of lesion in a patient based solely on the image.

Abstract: A system and method for collecting evidence pertaining to relationships between biomolecules and a disease, or other clinical condition, wherein biomolecules associated with the disease or condition identified, and ontologies relating to the biomolecules, disease or condition, and a predicate relationship therebetween are generated (or input to a processing system). Triplets, subject/predicate/object, for example, biomolecule/relationship/disease, are constructed by processing the ontologies. The triplets are used to search a body of relevant evidence to extract pertinent data from the body of relevant data based on the triplets. The system and method of the invention is used to provide researchers in the field of molecular diagnostics with biological evidence for or against statistical predictions.

Abstract: A user interface for a TV recommender system includes a display screen having a first region for displaying a rating derived from a previously defined TV viewing preference profile contained in the recommender system; and a second region displaying preference settings in the profile which were used to derive the rating. The user interface enables the preference settings to be changed if the rating derived by the profile is incorrect. Additionally, the user interface allows for new features to be added to the profile, which were not previously a part of the profile.

Abstract: A method for operating a neural network, and a program and apparatus that operate in accordance with the method. The method comprises the steps of applying data indicative of predetermined content, derived from an electronic signal including a representation of the predetermined content, to an input of at least one neural network, to cause the at least one network to generate at least one output indicative of either a detection or a non-detection of the predetermined content. Each neural network has an architecture specified by at least one corresponding parameter. The method also comprises a step of evolving the at least one parameter to modify the architecture of the at least one neural network, based on the at least one output, to increase an accuracy at which that at least one neural network detects the predetermined content indicated by the data.

Abstract: A system and method for subscribing TV programs according to the preferences of the user based on the user's past viewing history. The system keeps track of all the programs watched by the user to generate a profile indicative of the frequency of a particular program being watched. Then, a plurality of subscription plans based on the viewer's viewing habit stored in the user profile is offered to the user, so that the user can selectively pay for the programs of his or her interest, instead of paying for the entire programs.

Abstract: A TV viewer profile initializer for reducing the time it takes for an implicit profiler-based TV recommender to produce accurate TV recommendations. The profiles initializer utilizes stereotype profiles from a substantial pool of TV viewing behavior of a representative number of TV viewers. By applying clustering methods to such data, stereotype profiles can emerge. New viewers are then be offered a selection of stereotype profiles to choose from to initialize their own personal TV viewing profile. Thus, a single choice will suffice to provide a predictable TV show recommender that is presumably fairly close to a viewer's own preferences. After this initialization, the profile can be adapted by the user's own viewing behavior to migrate from the initial stereotype towards a more accurate profile of the user.

Abstract: A user interface for a TV recommender system includes a display screen having a first region for displaying a rating derived from a previously defined TV viewing preference profile contained in the recommender system; and a second region displaying preference settings in the profile which were used to derive the rating. The user interface enables the preference settings to be changed if the rating derived by the profile is incorrect. Additionally, the user interface allows for new features to be added to the profile, which were not previously a part of the profile. Further, a method for correcting a previously defined TV viewing preference profile used in a TV recommender system to more accurately reflect a user's preferences.