Abstract: When evaluating patient cases to determine complexity thereof, a computer-aided stratification technique is applied to analyze historical patient case diagnoses and correctness thereof in order to calculate a stratification score (20) for each of a plurality of abnormality types and/or anatomical locations. When a new patient case is received, the computer-aided stratification technique is applied to evaluate the patient case in view of historical data and assign a stratification score thereto. A ranked list (21) of current patient cases can be generated according to stratification scores, and physician workload can be adjusted as a function thereof so that workload is balanced across physicians and/or according to physician experience level.

Abstract: A clinical decision support (CDS) system comprises: a case grouping sub-system (10) including a graphical user interface (30) that is operative to simultaneously display data representing a plurality of patient cases and further configured to enable a user to group selected patient cases represented by the simultaneously displayed data into clinically related groups (32) as selected by the user; a probative features determination sub-system (12) that is operative to determine probative features (44) that correlate with the clinically related groups; and a CDS user interface (16) that is operative to receive current patient data relating to a current patient case and to output clinical decision support information based on values of the probative features determined from the received current patient data.

Abstract: A medical selection system 100 for generating selection data includes a user input 110 for enabling a user to establish a selection of one or more medical images amongst a plurality of medical images 182 for establishing the one or more medical images as baseline images for use in a follow-up examination of a patient. A processor 120 generate selection data 132 being indicative of said selection, and includes selection metadata in the selection data for enabling associating the selection data with the plurality of medical images. An output 130 provides the selection data to a medical processing system 150 for enabling the medical processing system to select, based on the selection data, the one or more medical images amongst the plurality of medical images for use as the baseline images in the follow-up examination of the patient.

Abstract: A computing device (126) includes a recommender (134) that evaluates at least one of a user interaction with a displayed image of a scan of an imaging examination protocol or information about the scan in an electronically formatted radiology report, and generates a signal including a recommendation to remove the scan only in response to at least one of the user interaction or the radiology report information satisfying predetermined criteria and a output device (140) that visually presents the signal, thereby visually presenting the recommendation.

Abstract: A system includes a modeler that generates a model which models a quality of findings in radiologist reports as a function of deposited dose of scans from which the radiologist reports are created and a dose optimizer that determines an optimal dose value for a planned scan based on the model and one or more optimization rules. A method includes generating a model which models a quality of findings in radiologist reports as a function of deposited dose of scans from which the radiologist reports are created and determining an optimal dose value tar a planned scan based on the model and one or more optimization rules.

Abstract: Methods are herein provided for decision support in diagnosis of a disease in a subject, and for extracting features from a multi-slice data set. Systems for computer-aided diagnosis are provided. The systems take as input a plurality of medical data and produces as output a diagnosis based upon this data. The inputs may consist of a combination of image data and clinical data. Diagnosis is performed through feature selection and the use of one or more classifier algorithms.

Abstract: A semiconductor structure includes a first-type doped semiconductor layer, a light emitting layer, a second-type doped semiconductor layer comprising AlxInyGa1-x-yN layers, at least one GaN based layer, and an ohmic contact layer. The light emitting layer is disposed on the first-type doped semiconductor layer, and the second-type doped semiconductor layer is disposed on the light emitting layer. The AlxInyGa1-x-yN layers stacked on the light emitting layer, where 0<x<1, 0?y<1, and 0<x+y<1, and the GaN based layer interposed between two of the AlxInyGa1-x-yN layers, and the ohmic contact layer is disposed on the AlxInyGa1-x-yN layers.

Abstract: A nitride semiconductor structure and a semiconductor light emitting device including the same are revealed. The nitride semiconductor structure mainly includes a stress control layer disposed between a light emitting layer and a p-type carrier blocking layer. The p-type carrier blocking layer is made from AlxGa1-xN (0<x<1) while the stress control layer is made from AlxInyGa1-x-yN (0<x<1, 0<y<1, 0<x+y<1). The light emitting layer has a multiple quantum well structure formed by a plurality of well layers and barrier layers stacked alternately. There is one well layer disposed between the two barrier layers. Thereby the stress control layer not only improves crystal quality degradation caused by lattice mismatch between the p-type carrier blocking layer and the light emitting layer but also reduces effects of compressive stress on the well layer caused by material differences.

Abstract: Methods are herein provided for decision support in diagnosis of a disease in a subject, and for extracting features from a multi-slice data set. Systems for computer-aided diagnosis are provided. The systems take as input a plurality of medical data and produces as output a diagnosis based upon this data. The inputs may consist of a combination of image data and clinical data. Diagnosis is performed through feature selection and the use of one or more classifier algorithms.

Abstract: A rapid screening device has a sensing unit, a processing unit and a carrier, the processing unit is connected to the sensing unit, the sensing unit and the processing unit are disposed on the carrier, the sensing unit captures an image of an eyeball and outputs an image signal of the eyeball, the image of the eyeball is resolved from the image signal of the eyeball, the processing unit retrieves a plurality of images from the sensing unit within a predetermined time interval and executes an algorithm to generate a calculated result by the images of the image signals of the eyeball, and the calculated result is used to diagnose or predict a disease.

Abstract: A system for suggesting autocompletion terms during text entry of a report. A text entry unit (2) for enabling a user to enter a text into a current report (1). A term selector (11) for selecting at least one frequently co-occurring term (12), based on an extracted term (8), the extracted term section (9), the current section (10), and a co-occurrence statistic (7). An indicator (13) provides an indication of the at least one frequently co-occurring term (12) to the user. A system for analyzing reports comprises a co-occurrence statistics generator (26) for generating a plurality of co-occurrence statistics, a co-occurrence statistic being indicative of a first term, a first section, a second term, a second section, and a frequency in which reports contain the first term in the first section in combination with the second term in the second section.

Abstract: A method for creating a report with an annotation includes receiving an input image to annotate. The method further includes comparing the input image with a set of previously annotated images. The method further includes generating a similarity metric for each of the previously annotated images based on a result of a corresponding comparison. The method further includes identifying a previously annotated image with a greatest similarity for each of a plurality of predetermined annotations. The method further includes visually displaying the identified image for each annotation along with the annotation. The method further includes receiving an input signal identifying one of the displayed images. The method further includes annotating the input image with the identified one of the displayed images. The method further includes generating, in an electronic format, a report for the input image that includes the identified annotation.

Abstract: This invention relates to a method and device for case-based decision support. It proposes that a case-based decision support system is trained on inputs from several radiologists in order to have a “baseline” system, and then the system provides an option to a radiologist to refine the baseline system based on his/her inputs which either refine weights of features for similarity distance computation directly or provide new similarity ground truth clusters. By enabling modifying the similarity distance computation based on user inputs, this invention adapts similarity ground truth to different users with different experience and/or different opinions.

Abstract: A semiconductor structure includes a first-type doped semiconductor layer, a light emitting layer, a second-type doped semiconductor layer comprising AlxInyGal-x-yN layers, at least one GaN based layer, and an ohmic contact layer. The light emitting layer is disposed on the first-type doped semiconductor layer, and the second-type doped semiconductor layer is disposed on the light emitting layer. The AlxInyGal-x-yN layers stacked on the light emitting layer, where 0<x<1, 0?y<1, and 0<x+y<1, and the GaN based layer interposed between two of the AlxInyGal-x-yN layers, and the ohmic contact layer is disposed on the AlxInyGal-x-yN layers.

Abstract: A nitride semiconductor structure and a semiconductor light emitting device including the same are revealed. The nitride semiconductor structure mainly includes a stress control layer disposed between a light emitting layer and a p-type carrier blocking layer. The p-type carrier blocking layer is made from AlxGa1-xN (0<x<1) while the stress control layer is made from AlxInyGa1-x-yN (0<x<1, 0<y<1, 0<x+y<1). The light emitting layer has a multiple quantum well structure formed by a plurality of well layers and barrier layers stacked alternately. There is one well layer disposed between the two barrier layers. Thereby the stress control layer not only improves crystal quality degradation caused by lattice mismatch between the p-type carrier blocking layer and the light emitting layer but also reduces effects of compressive stress on the well layer caused by material differences.

Abstract: A method includes obtaining image data for a patient. The image data corresponds to acquisition data from an imaging acquisition from a set of planned image acquisitions in an examination plan for the patient. The method further includes analyzing the image data with a processor based on an imaging practice guideline and producing electronically formatted data indicative of the analysis. The processor generates a signal indicative of a recommendation of a change to the examination plan based on the data indicative of the analysis.

Abstract: A nitride semiconductor structure and a semiconductor light emitting device including the same are revealed. The nitride semiconductor structure mainly includes a stress control layer disposed between a light emitting layer and a p-type carrier blocking layer. The p-type carrier blocking layer is made from AlxGa1-xN (0<x<1) while the stress control layer is made from AlxInyGa1-x-yN (0<x<1, 0<y<1, 0<x+y<1). The light emitting layer has a multiple quantum well structure formed by a plurality of well layers and barrier layers stacked alternately. There is one well layer disposed between the two barrier layers. Thereby the stress control layer not only improves crystal quality degradation caused by lattice mismatch between the p-type carrier blocking layer and the light emitting layer but also reduces effects of compressive stress on the well layer caused by material differences.

Abstract: When evaluating patient cases to determine complexity thereof, a computer-aided stratification technique is applied to analyze historical patient case diagnoses and correctness thereof in order to calculate a stratification score (20) for each of a plurality of abnormality types and/or anatomical locations. When a new patient case is received, the computer-aided stratification technique is applied to evaluate the patient case in view of historical data and assign a stratification score thereto. A ranked list (21) of current patient cases can be generated according to stratification scores, and physician workload can be adjusted as a function thereof so that workload is balanced across physicians and/or according to physician experience level.

Abstract: A magnetic resonance imaging scan using a MR scanner receives via a user interface a MR imaging protocol categorizable into a MR scan type of a predefined set of MR scan types. Further, a database is queried by providing to the database scan information permitting the database to identify the MR scan type of the MR imaging protocol. Statistical information on the MR scan type which can include statistics on modifications of individual scan parameters of the MR scan type is received from a database, and the statistical information is provided to the user interface. Modifications of the MR imaging protocol can be received from the user interface, resulting in a modified MR imaging protocol, according to which the MR imaging scan can be performed.

Abstract: The present invention provides a rapid screening device for brain disease to diagnose a patient's disease of cranial nerves by the states of the patient's eyeball. The rapid screening device for brain disease comprises a sensing unit, a processing unit and a carrier. The sensing unit can capture an image of the patient's eyeball. The sensing unit outputs an image signal of the eyeball, wherein the image of at least one eyeball can be resolved from the image signal of the eyeball. The processing unit is connected to the sensing unit. The processing unit retrieves a plurality of images from the sensing unit within a predetermined time interval, and the processing unit executes an algorithm to generate a calculated result by the images of the image signals of the eyeball. The carrier is provided with the sensing unit and the processing unit, wherein the calculated result is used to diagnose or predict that the disease happens to the patient.