Abstract: Systems and methods are disclosed for processing digital images to identify diagnostic tests, the method comprising receiving one or more digital images associated with a pathology specimen, determining a plurality of diagnostic tests, applying a machine learning system to the one or more digital images to identify any prerequisite conditions for each of the plurality of diagnostic tests to be applicable, the machine learning system having been trained by processing a plurality of training images, identifying, using the machine learning system, applicable diagnostic tests of the plurality of diagnostic tests based on the one or more digital images and the prerequisite conditions, and outputting the applicable diagnostic tests to a digital storage device and/or display.

Abstract: Disclosed herein are systems and methods based on tumor infiltrating leukocyte (TIL) fractal geometry to predict clinical implications in breast cancer samples. Using machine learning techniques, an algorithmic classifier is constructed and trained on a cohort of tumor images (e.g. radiographic, immunohistochemical (IHC), and H&E images) to discriminate between TILs and cancer cells, and breast cancer samples are classified based on TIL fractal geometry/anatomic distribution in the tumor stroma. Fractal geometry-directed reassessment of classifications may prompt tumor type reclassification resulting in altered cancer therapy.

Abstract: Systems and methods are disclosed for processing digital images to identify diagnostic tests, the method comprising receiving one or more digital images associated with a pathology specimen, determining a plurality of diagnostic tests, applying a machine learning system to the one or more digital images to identify any prerequisite conditions for each of the plurality of diagnostic tests to be applicable, the machine learning system having been trained by processing a plurality of training images, identifying, using the machine learning system, applicable diagnostic tests of the plurality of diagnostic tests based on the one or more digital images and the prerequisite conditions, and outputting the applicable diagnostic tests to a digital storage device and/or display.

Abstract: Systems and methods are disclosed for processing digital images to identify diagnostic tests, the method comprising receiving one or more digital images associated with a pathology specimen, determining a plurality of diagnostic tests, applying a machine learning system to the one or more digital images to identify any prerequisite conditions for each of the plurality of diagnostic tests to be applicable, the machine learning system having been trained by processing a plurality of training images, identifying, using the machine learning system, applicable diagnostic tests of the plurality of diagnostic tests based on the one or more digital images and the prerequisite conditions, and outputting the applicable diagnostic tests to a digital storage device and/or display.

Abstract: Systems and methods are disclosed for processing digital images to identify diagnostic tests, the method comprising receiving one or more digital images associated with a pathology specimen, determining a plurality of diagnostic tests, applying a machine learning system to the one or more digital images to identify any prerequisite conditions for each of the plurality of diagnostic tests to be applicable, the machine learning system having been trained by processing a plurality of training images, identifying, using the machine learning system, applicable diagnostic tests of the plurality of diagnostic tests based on the one or more digital images and the prerequisite conditions, and outputting the applicable diagnostic tests to a digital storage device and/or display.

Abstract: Systems and methods are disclosed for processing digital images to identify diagnostic tests, the method comprising receiving one or more digital images associated with a pathology specimen, determining a plurality of diagnostic tests, applying a machine learning system to the one or more digital images to identify any prerequisite conditions for each of the plurality of diagnostic tests to be applicable, the machine learning system having been trained by processing a plurality of training images, identifying, using the machine learning system, applicable diagnostic tests of the plurality of diagnostic tests based on the one or more digital images and the prerequisite conditions, and outputting the applicable diagnostic tests to a digital storage device and/or display.

Abstract: The system comprises a monitoring device, one acquisition unit and respective method for monitoring and registering the position of an individual. This disclosure is intended for the following applications: 1) prevention or assistance in the treatment of pressure ulcers (or decubitus ulcers), common in immobile patients (2) or wheelchairs users, 3) monitoring of patients suffering from dementia (which makes them do some actions (for instance: getting up from a chair) without being aware of them, and that can suffer serious accidents due to that), 4) fall detection and 5) involuntary body movements (e.g. epileptic attack). The monitoring device comprises an inertial system, with 3 or more accelerometers; a directional system, with 3 or more magnetometers; a communication module; and a processor module to obtain and communicate the inclination and direction of the device, when coupled to an individual.

Abstract: The disclosed subject matter relates to a portable and autonomous device and corresponding method for the measurement, recording and calculation of dynamic parameters of the pedestrian locomotion of its bearer. The method hereby disclosed allows determining the distance effectively travelled, the velocity of displacement and the pressures exerted on the contact surface of the lower limb with the ground, during the pedestrian locomotion, according to its different phases. Through sensors strategically placed, accelerations, angular velocities and pressures are measured and recorded on the control unit. The device disclosed includes a processing unit that implements the method disclosed and a communication unit to transfer to an external unit the calculated parameters. The disclosed invention can be used in applications that involve monitoring parameters of the locomotion activity or daily ambulation of its bearer, in the areas of health and sports or in any physical and occupational activities.

Abstract: This invention provides a mobile aerosol generator which enables the vehicle operator to remotely reposition the droplet launch trajectory during normal operation of the generator and the vehicle. Azimuth and elevation launch directions are controlled separately or simultaneously by the vehicle operator using a remote control box. The repositioning ranges are about 180 degrees in azimuth included angle centered about a preset position, normally the direction of vehicle travel, and from about 60 degrees above to about 15 degrees below the plane of vehicle travel. A turntable like actuator provides azimuth repositioning and a linear actuator coupled to the nozzle provides elevation repositioning. Tubular nozzle support structure also acts as conduit for pressurized air to a two-fluid nozzle. A liquid delivery system provides a controlled amount of liquid to the nozzle where the fluid is sheared into droplets using pressurized air.