Abstract: An electrocardiogram (ECG) interpretation system is operable to receive a captured image of an ECG printout. A waveform detection function is performed on the captured image to determine a plurality of locations of a plurality of ECG waveforms in the captured image. A plurality of waveform images are generated by partitioning the captured image based on the plurality of locations, where each of the plurality of waveform images includes one of the plurality of ECG waveforms. A plurality of pseudo-raw ECG signal data is generated by performing a signal reconstruction function on each of the plurality of waveform images, where each of the plurality of pseudo-raw ECG signal data corresponds to one of the plurality of waveform images. Diagnosis data is generated by performing a diagnosing function on the plurality of pseudo-raw ECG signal data. The diagnosis data is transmitted to a client device for display via a display device.

Abstract: A dressing assembly for use with a reduced pressure treatment system, the dressing assembly develops a directed force under reduced pressure. The directed force may be a radial force or a closing force. The dressing assembly includes a shaped dressing bolster having a shaped extremity that is operable to evenly deliver the radial force and to distribute reduced pressure. Numerous shapes may be used for the shaped extremity. The dressing assembly may further include an over-drape to assist in creating a seal over the shaped dressing bolster and against a portion of a patient's epidermis.

Abstract: A medical scan diagnosing system is operable to receive a medical scan. Diagnosis data of the medical scan is generated by performing a medical scan inference function on the medical scan. The first medical scan is transmitted to a first client device associated with a user of the medical scan diagnosing system in response to the diagnosis data indicating that the medical scan corresponds to a non-normal diagnosis. The medical scan is displayed to the user via an interactive interface displayed by a display device corresponding to the first client device. Review data is received from the first client device, where the review data is generated by the first client device in response to a prompt via the interactive interface. Updated diagnosis data is generated based on the review data. The updated diagnosis data is transmitted to a second client device associated with a requesting entity.

Abstract: The present disclosure relates to a curable precursor of an adhesive composition, comprising: a) a (meth)acrylate-based (co)polymer base component comprising the free-radical (co)polymerization reaction product of a (co)polymerizable material comprising: i. C1-C32 acrylic acid ester monomer units; ii. optionally, C1-C18 methacrylic acid ester monomer units; and iii. optionally, ethylenically unsaturated monomer units having a functional group and which are copolymerizable with monomer units (i) and/or (ii); b) a crosslinker for the (meth)acrylate-based (co)polymer base component, which comprises at least one acid-functional group derived from phosphoric acid and at least one free-radical (co)polymerizable reactive group; c) a polyether oligomer having a number average molecular weight of at least 2000 g/mol and which comprises at least one free-radical (co)polymerizable reactive group; and d) a thermally conductive particulate material.

Abstract: An optically anisotropic polymer thin film includes a crystallizable polymer and an additive configured to interact with the polymer (e.g., via ?-? interactions) to facilitate chain alignment and, in some examples, create a higher crystalline content within the polymer thin film. The polymer thin film may be characterized by a bimodal molecular weight distribution where the molecular weight of the additive may be less than approximately 50% of the molecular weight of the crystallizable polymer. Example crystallizable polymers include polyethylene naphthalate, polyethylene terephthalate, polybutylene naphthalate, polybutylene terephthalate, as well as derivatives thereof. Example additives, which may occupy up to approximately 10 wt. % of the polymer thin film, include aromatic ester oligomers, aromatic amide oligomers, and polycyclic aromatic hydrocarbons, for example. The optically anisotropic polymer thin film may be characterized by a refractive index greater than approximately 1.

Abstract: An electronic component and a method of manufacturing an electronic component, the method including surface mounting electronic components to a printed circuit board (PCB), applying a flip-chip die integrated circuit (IC) to the PCB and underfilling the flip-chip IC to secure the PCB. The method also includes sintering a copper block to the PCB, where the copper block is in thermal communication with the IC and acts as a thermal path for removing heat generated by the flip-chip IC.

Abstract: A method for displaying a virtual item includes: displaying a first virtual environment picture, the first virtual environment picture displaying a second virtual item in an effective state; controlling, in response to a use instruction, a target virtual character to use an equipped first virtual item; displaying, in response to the second virtual item being located within a first influence range of the first virtual item, that the second virtual item is switched from the effective state to an ineffective state; and displaying, in response to satisfying a restoration condition, that the second virtual item is switched from the ineffective state to the effective state.

Abstract: A lesion tracking system is operable to detect a first lesion in a first subset of image slices of a first medical scan corresponding to a patient via artificial intelligence by utilizing a computer vision model. The first lesion is detected in a second subset of image slices of a second medical scan corresponding to the patient via artificial intelligence by utilizing the computer vision model. A lesion diameter measurement function is performed on at least one of the first subset of image slices to generate a first lesion diameter measurement, and is performed on at least one of the second subset of image slices to generate a second lesion diameter measurement. RECIST evaluation data is generated based on a computed difference between the first lesion diameter measurement and the second lesion diameter measurement. The RECIST evaluation data is transmitted for display via a display device.

Abstract: A multi-model medical scan analysis system is operable to generate a plurality of training sets from a plurality of medical scans. Each of a set of sub-models is generated by performing a training step on a corresponding one of the plurality of training sets of the plurality of medical scans. A set of abnormality data is generated by applying a subset of a set of inference functions on a new medical scan. The subset of the set of inference functions utilize the subset of the set of sub-models, and each of the set of abnormality data is generated as output of performing one of the subset of the set of inference functions. The multi-model medical scan analysis system is further operable to generate final abnormality data that includes a global probability indicating a probability that any abnormality is present based on the set of abnormality data.

Abstract: A reduced-pressure system for treating tissue, such as damaged subcutaneous tissue, includes a shaped dressing bolster for placing on the patient's epidermis and substantially sized to overlay the damaged subcutaneous tissue. The system further includes a sealing subsystem for providing a fluid seal over the shaped dressing bolster and a portion of the patient's epidermis, and a reduced-pressure subsystem for delivering a reduced pressure to the sealing subsystem. The reduced-pressure system may develop a force, which may include a vertical force that is realized at tissue site deeper than the epidermis or a closing force directed towards the incision. The shaped dressing bolster is shaped to evenly distribute the force. Other methods and systems are included.

Abstract: A model-assisted annotating system is operable to receive a first set of annotation data, corresponding to a broad type of annotation data output. A first training step is performed to train a computer vision model using the first set of annotation data. A second set of annotation data corresponding to the broad type of annotation data output is generated performing an inference function utilizing the computer vision model on medical scans. Additional annotation data further specifies the broad type of annotation data output is received. A second training step is performed to generate an updated computer vision model using set of additional annotation data. A third set of annotation data corresponding to the specified type of annotation data output is generated by performing an updated inference function utilizing the updated computer vision model on medical scans.

Abstract: A medical scan quality assurance system is operable to utilize artificial intelligence to train at least one computer vision model based on a training set of medical scans. A set of medical scans are received. Quality assurance data is generated for the set of medical scans utilizing artificial intelligence by performing at least one quality assurance function on the set of medical scans by utilizing the at least one computer vision model. A first medical scan is identified in the set of medical scans to include an artifact, detected by performing the at least one quality assurance function, that is determined to obscure at least a threshold percentage of a key anatomical part based on the quality assurance data. An artifact obstruction notification indicating the first medical scan is generated for transmission to a client device for display.

Abstract: A method includes generating first contrast significance data for a first computer vision model generated from a first training set of medical scans. First significant contrast parameters are identified based on the first contrast significance data. A first re-contrasted training set is generated based on performing a first intensity transformation function on the first training set of medical scans, where the first intensity transformation function utilizes the first significant contrast parameters. A first re-trained model is generated from the first re-contrasted training set, which is associated with corresponding output labels based on abnormality data for the first training set of medical scans. Re-contrasted image data of a new medical scan is generated based on performing the first intensity transformation function. Inference data indicating at least one abnormality detected in the new medical scan is generated based on utilizing the first re-trained model on the re-contrasted image data.

Abstract: A method includes generating a longitudinal lesion model by performing a training step on a plurality of sets of longitudinal data. Dates of medical scans of different ones of the plurality of sets of longitudinal data have relative time differences corresponding to different time spans, and each set of the plurality of sets of longitudinal data corresponds to one of a plurality of different patients. The longitudinal lesion model is utilized to perform an inference step on a received medical scan to generate, for a lesion detected in the received medical scan, a plurality of lesion change prediction data for a corresponding plurality of different projected time spans ending after the current date. At least one of the plurality of lesion change prediction data is transmitted for display.

Abstract: Provided are a resistant protein for use in herbicide dicamba, encoding gene and application thereof, the gene comprising: (a) a nucleotide sequence of an amino acid sequence as shown in SEQ ID NO: 2; or (b) a nucleotide sequence which is complementary to the nucleotide sequence as defined by (a) under stringent conditions; or (c) a nucleotide sequence as shown in SEQ ID NO: 1.

Abstract: The present disclosure provides a variable-frequency compressor with adaptive heating power control and a method for operating the same. According to an embodiment of the present disclosure, the variable-frequency compressor includes: a compression unit, for compressing a medium entering the variable-frequency compressor; a motor, including a stator and a rotor, for driving the compression unit; and a controller, configured to adaptively control a heating power of a winding of the stator according to information of the variable-frequency compressor.

Abstract: Compositions are provided including an uncrosslinked thermoplastic nitrogen-containing matrix material and composite particles distributed in the matrix material. The composite particles each include a chemical blowing agent particle encapsulated within a shell including an uncrosslinked thermoplastic material. The uncrosslinked thermoplastic material exhibits at least a certain minimum complex viscosity at a decomposition temperature of the chemical blowing agent particle. Also described are foam compositions and particles including the foam compositions, such as a sheet or multilayer construction. Composite particles are further provided. Methods of making the foam compositions are additionally described herein. Also, polishing pads, polishing systems, and methods of polishing a substrate are provided.

Abstract: A medical scan header standardization system is operable to determine a plurality of counts for a plurality of entries of at least one of a standard set of fields for headers of a plurality of medical images. A standard set of header entries is determined for at least one of the standard set of fields based on including ones of the entries for the each of the standard set of fields with counts of the plurality of counts that compare favorably to a threshold. One of the standard set of header entries is selected to replace an entry of a field of a header of a medical image. A computer vision model is trained utilizing a training set of images that includes the medical image and the selected one of the standard set of header entries. Inference data for at least one new medical scan is generated based on utilizing the computer vision model.

Abstract: A clinical trial re-evaluation system is operable to perform at least one assessment function on a set of medical scans for each of a first subset of a set of patients of a failed clinical trial to generate automated assessment data for each of the first subset of the set of patients. The first subset of the set of patients corresponds to a subset of human assessment data determined to have failed to meet criteria of the clinical trial. Patient re-evaluation data is generated for each of the first subset of the set of patients by comparing the automated assessment data to the criteria. The patient re-evaluation data for a second subset of the first subset of the set of patients indicates the automated assessment data passes the criteria. Trial re-evaluation data is generated based on the patient re-evaluation data for transmission to a computing device for display.