Abstract: A method (100) for determining a baseline creatinine value for a subject, comprising: obtaining (130) a set of features about the subject; analyzing (140), using a trained baseline creatinine determination model, the obtained set of features to generate a baseline creatinine value for the subject; reporting (150), via a user interface, the generated baseline creatinine value for the subject.

Abstract: An apparatus (10) for predicting patient respiratory stability includes a patient data memory (24) which stores patient data for a patient (12) and an analyzer (34) in communication with the memory computes a measure of patient respiratory stability. The analyzer applies one or more rules to the patient data that are based on a plurality of parameters which in combination, have been identified as being predictive of patient respiratory instability, such as mean airway pressure (MAWP), plateau pressure (PP), arterial oxygen saturation (SaO2 or SpO2), and heart rate (HR). Based on the application of the rules, the analyzer determines the measure of patient respiratory stability.

Abstract: Cross over (S560) in a genetic algorithm (128) is adapted for deriving an optimal mask (S540), or set of segments of a line. Each mask of a chromosome is subject to cross over with the respective mask of the other parent. Any overlapping part, whether a filtering (320) or pass-through part (350), is retained in the child (334) to preserve commonality. The part is preferably, potentially extended, according to one parent or the other, as decided pseudo-randomly (430). In a preferred application, spectrums of candidate blood constituents are masked for fitting to ensemble spectrums of test blood samples (S610, S620). The developed masks are applicable to constituent spectrums to create masked spectrums (S710) which are then applicable to an actual blood sample to be analyzed (S720).

Abstract: An apparatus (10) for predicting patient respiratory stability includes a patient data memory (24) which stores patient data for a patient (12) and an analyzer (34) in communication with the memory computes a measure of patient respiratory stability. The analyzer applies one or more rules to the patient data that are based on a plurality of parameters which in combination, have been identified as being predictive of patient respiratory instability, such as mean airway pressure (MAWP), plateau pressure (PP), arterial oxygen saturation (SaO2 or SpO2), and heart rate (HR). Based on the application of the rules, the analyzer determines the measure of patient respiratory stability.

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: Cross over (S560) in a genetic algorithm (128) is adapted for deriving an optimal mask (S540), or set of segments of a line. Each mask of a chromosome is subject to cross over with the respective mask of the other parent. Any overlapping part, whether a filtering (320) or pass-through part (350), is retained in the child (334) to preserve commonality. The part is preferably, potentially extended, according to one parent or the other, as decided pseudo-randomly (430). In a preferred application, spectrums of candidate blood constituents are masked for fitting to ensemble spectrums of test blood samples (S610, S620). The developed masks are applicable to constituent spectrums to create masked spectrums (S710) which are then applicable to an actual blood sample to be analyzed (S720).

Abstract: Method and system for determining a norm to apply to a patient being examined in which at least one physical characteristic of the patient is determined from the examination and guidelines relating thereto are obtained. Information about the patient other than from the examination and established norms for each characteristic are also obtained. An established norm to be applied to the patient is selected based on the determination of the characteristic(s), the guidelines relating to the determination thereof, and the information about the patient other than from the examination. The selection of the norm is performed by an inference engine. The norm is applied to the characteristic, e.g., a measured anatomical feature, to obtain a normal value therefor. The measured anatomical feature is compared to the normal value to determine whether it is indicative of a normal or abnormal condition.

Abstract: A system is provided for guiding the selection of a value for each of a plurality of parameters needed to perform a procedure with a medical system (100). The system includes a first knowledge base (210) comprising procedures and treatment regimes, a second knowledge base (212) comprising patient information and therapy history, and a third knowledge base (214) comprising clinical guidelines. A domain ontology (220) provides the semantic mapping between information in the first, second, and third knowledge bases. A system configuration database (226) contains physical characteristics pertaining to the medical system and a system characteristics database (228) contains mathematical formulas and algorithms for calibrating the medical system based on the data in the system configuration database.

Abstract: A system and method for directing an incoming telephone call. The system comprises a control unit that receives images associated with two or more regions of a local environment. The two or more regions are each serviced by a respective telephone extension. The control unit processes the images to identify, from a group of known persons associated with the local environment, any one or more known persons located in the respective regions. For each known person so identified, an indicium is generated that associates the known person with the respective region in which the known person is located.