Abstract: An AI system may receive an image. The AI system may include a first AI model trained using labeled training images including images from prior mammograms to predict cancer and a second AI model trained using labeled training images including images from current mammograms to classify mammogram images. The second AI model may be initialized using the weights of the first AI model using transfer learning. The AI system may receive a classification output indicating a likely current breast cancer diagnosis or a likelihood of the user to develop breast cancer in the future.

Abstract: An approach for training, on a computer, one or more deep learning algorithms with a plurality of mammograms with known outcomes based, at least in part, on using a set of mammograms of each patient in the plurality of mammograms. The approach includes receiving a first set of mammograms of a first patient. The first set of mammograms includes an unevaluated mammogram of the first patient and a set of prior mammograms of the first patient. The approach includes the trained convolutional neural network extracting the set of features from each mammogram of the set of mammograms of the first patient. Furthermore, the approach includes using a second deep learning algorithm of the one or more deep learning algorithms to perform an evaluation of the unevaluated mammogram of the first patient based, at least in part, on the set of prior mammograms of the first patient.

Abstract: Automated assignment of confidence levels to medical diagnoses in a machine learning training data with respect to annotations made upon review of medical records such as x-ray films and test results. Confidence levels support machine learning for computer-aided diagnostic activity.

Abstract: The invention includes a device for smoking smokeable material. The device has a housing, a rotatable shaft for driving smokeable material towards the first end of the housing as the smokeable material is smoked, at least one radial hole through the shaft for passage of smokeable material from the burning section of the housing into the longitudinal hole of the rotatable shaft.

Abstract: An embodiment of the invention may include a method, computer program product and computer system for object detection and identification. The method, computer program product and computer system may include computing device which may receive an image from an imaging device. The image may be a medical image. The computing device may detect one or more potential indicators of disease in the image using a first algorithm and determine areas of potential disease in the image using an artificial intelligence algorithm. The computing device may determine a correlation between the determined areas of potential disease in the image and the one or more potential indicators of disease for the image. The computing device may, in response to determining a positive correlation, identify one or more of the potential indicators of disease for annotation and generate a report indicating one or more potential indicators of disease was found in the image.

Abstract: An embodiment of the invention may include a method, computer program product and computer system for image artifact removal. The method, computer program product and computer system may include computing device which may receive a primary image and analyze the primary image for global artifacts and local artifacts. The computing device may, in response to identifying a global artifact in the primary image, generate a secondary image with the global artifact removed utilizing a first generative adversarial network. The computing device may, in response to identifying a local artifact in the primary image, generate a patch with the local artifact removed utilizing a second generative adversarial network. The computing device may generate a hybrid image containing a reduction of global artifacts and a reduction of local artifacts by combining the secondary image and the patch utilizing a hybrid generative adversarial network.

Abstract: A method, computer system, and a computer program product for case-adaptive image quality assessment is provided. The present invention may include detecting a current set of features in a current exam associated with a patient. The present invention may also include calculating a current set of quality measurements for the current exam based on the detected current set of features. The present invention may further include in response to determining that the calculated current set of quality measurements for the current exam is below a patient-specific image quality threshold defined by at least one prior exam associated with the patient, automatically registering a negative quality assessment for the current exam associated with the patient.

Abstract: An electronic cigarette comprising an atomizer is provided. The electronic cigarette includes an inner core assembly configured to receive liquid and provide the liquid through at least one opening in the inner core assembly. The inner core assembly includes a heater having a noncylindrical shape, in one embodiment having hexagonal shape in a sinusoidal wave pattern with rounded corners.

Abstract: A hair styling apparatus is provided including a brush head, a plurality of tines located on the brush head, and a series of movable linearly arranged prongs having an angled orientation with respect to the brush head. A user causing movement of the linearly arranged prongs serves to secure the user' s hair against a subset of the plurality of tines.

Abstract: A vaporizer is provided, including a body, a concentrate chamber provided within the body and including at least one chamber aperture, a concentrate pusher configured to push material through the concentrate chamber, a heating element having at least one element aperture, the heating element positioned proximate the at least one chamber aperture and configured to heat material pushed through the concentrate chamber, and a power source configured to apply power to the heating element.

Abstract: An embodiment of the invention may include a method, computer program product and computer system for image artifact removal. The method, computer program product and computer system may include computing device which may receive a primary image and analyze the primary image for global artifacts and local artifacts. The computing device may, in response to identifying a global artifact in the primary image, generate a secondary image with the global artifact removed utilizing a first generative adversarial network. The computing device may, in response to identifying a local artifact in the primary image, generate a patch with the local artifact removed utilizing a second generative adversarial network. The computing device may generate a hybrid image containing a reduction of global artifacts and a reduction of local artifacts by combining the secondary image and the patch utilizing a hybrid generative adversarial network.

Abstract: An electronic cigarette comprising an atomizer is provided. The electronic cigarette includes an inner core assembly configured to receive liquid and provide the liquid through at least one opening in the inner core assembly. The inner core assembly includes a heater having a noncylindrical shape, in one embodiment having hexagonal shape in a sinusoidal wave pattern with rounded corners.

Abstract: A method, computer system, and a computer program product for case-adaptive image quality assessment is provided. The present invention may include detecting a current set of features in a current exam associated with a patient. The present invention may also include calculating a current set of quality measurements for the current exam based on the detected current set of features. The present invention may further include in response to determining that the calculated current set of quality measurements for the current exam is below a patient-specific image quality threshold defined by at least one prior exam associated with the patient, automatically registering a negative quality assessment for the current exam associated with the patient.

Abstract: An embodiment of the invention may include a method, computer program product and computer system for object detection and identification. The method, computer program product and computer system may include computing device which may receive an image from an imaging device. The image may be a medical image. The computing device may detect one or more potential indicators of disease in the image using a first algorithm and determine areas of potential disease in the image using an artificial intelligence algorithm. The computing device may determine a correlation between the determined areas of potential disease in the image and the one or more potential indicators of disease for the image. The computing device may, in response to determining a positive correlation, identify one or more of the potential indicators of disease for annotation and generate a report indicating one or more potential indicators of disease was found in the image.

Abstract: Mechanisms are provided for implementing a patient complexity classification (PCC) computing system. The PCC computing system receives medical image study data for a patient that comprises one or more medical image data structures and one or more corresponding medical image metadata data structures. A natural language processing engine of the PCC computing system performs natural language processing on the medical image metadata data structure to extract features indicative of at least one of patient or medical image characteristics. A complexity classifier of the PCC computing system evaluates the extracted features to determine a patient complexity indicating a complexity of a medical condition of the patient. Routing logic associated with the PCC computing system routes the one or more medical image data structures and one or more corresponding medical image metadata data structures to one or more downstream patient evaluation computing systems based on the determined patient complexity.

Abstract: A filter device including a Bernoulli element is provided. The filter device includes a housing, a plurality of permeable membranes positioned in association with the housing to create a plurality of chambers in the housing, and a Bernoulli element positioned within one chamber, wherein the Bernoulli element causes airflow and pressure to vary within the one chamber when fluid comprising smoke is drawn into the filter device.

Abstract: A hair styling apparatus is provided including a brush head, a plurality of tines located on the brush head, and a series of movable linearly arranged prongs having an angled orientation with respect to the brush head. A user causing movement of the linearly arranged prongs serves to secure the user' s hair against a subset of the plurality of tines.

Abstract: Mechanisms are provided for implementing a patient complexity classification (PCC) computing system. The PCC computing system receives medical image study data for a patient that comprises one or more medical image data structures and one or more corresponding medical image metadata data structures. A natural language processing engine of the PCC computing system performs natural language processing on the medical image metadata data structure to extract features indicative of at least one of patient or medical image characteristics. A complexity classifier of the PCC computing system evaluates the extracted features to determine a patient complexity indicating a complexity of a medical condition of the patient. Routing logic associated with the PCC computing system routes the one or more medical image data structures and one or more corresponding medical image metadata data structures to one or more downstream patient evaluation computing systems based on the determined patient complexity.

Abstract: An apparatus for rolling papers into a non-cylindrical orientation is provided. The apparatus includes a rotatable non-cylindrical workpiece having a plurality of openings provided therein, a surface comprising a receiving indentation configured to receive and fit the rotatable non-cylindrical workpiece, a suction producing arrangement connected to the rotatable non-cylindrical workpiece, and a rolling paper. The suction producing arrangement draws air through the plurality of openings while the rotatable non-cylindrical workpiece rotates such that the drawn air draws the rolling paper toward and around the rotatable non-cylindrical workpiece, the rotation causing the rolling paper and a quantity of adhesive applied to the rolling paper to form a completed non-cylindrical rolling paper product.

Abstract: A method, computer system, and a computer program product for automatic labeling to train a machine learning algorithm is provided. The present invention may include labeling a medical image with at least one finding from a corresponding medical report. The present invention may include determining a localization information from the labeled medical image. The present invention may include training the machine learning algorithm with the determined localization information. The present invention may include detecting at least one candidate in a test medical image. The present invention may include generating a discrepancy list between the at least one detected candidate in the test medical image and at least one human-reported finding in a corresponding test medical report. The present invention may include, in response to determining that the generated discrepancy list is above a threshold, retraining the trained machine learning algorithm until the generated discrepancy list is below the threshold.