Abstract: The present invention is related to correct the errors in instruments, operation, and others using intelligent monitoring structures and machine learning, and others.

Abstract: A method of assaying an analyte in a sample is disclosed. The method includes having a sample holder with a sample contact area for contacting a sample with an analyte, having a plurality of calibration structures on the sample contact area of the sample holder, imaging a part of the sample contact area that has the calibration structures, and using an algorithm that includes an image, calibration structures in the image, and artificial intelligence and/or machine learning to identify the analyte and/or determine the analyte concentration.

Abstract: The disclosure provides a method for identifying a bio-entity including a cell type and count in a sample. The method includes: providing a device comprising a first plate, a second plate, and a patterned structural element; depositing the sample between the first and second plates; reducing the spacing of the first and second plates so that the first and second plates are in a closed configuration to compress the sample into a layer; and imaging the sample to obtain an image; and measuring and analyzing the image against a database generated with a machine learning model to obtain the bio-entity of the sample. The sample can be a blood sample, and the method can be a white blood cell differential test conducted with a mobile phone.

Abstract: The present invention is related to, among other things, the devices and methods that improve the accuracy and reliability of an assay, even when the assay device and/or the operation of the assay device has certain errors, and in some embodiments, the errors are random. One aspect of the present invention is to overcome the random errors or imperfections of an assay device or the operation of the assay device by measuring, in addition to measuring the analyte in a sample to generate an analyte test result, the trustworthiness of the analyte test result. The analyte test result will be reported, only when the trustworthiness meets a predetermined threshold, otherwise the analyte test result will be discarded. Various of parameter variation have been used for test trustworthy determination.

Abstract: Disclosed is an apparatus and method for imaging: a side-view of a object on a surface, a Contact Angle of a liquid object, the color of an object, or combinations thereof.

Abstract: The present invention is related to, among other things, the devices and methods that improve the accuracy and reliability of an assay, even when the assay device and/or the operation of the assay device has certain errors, and in some embodiments the errors are random.

Abstract: One aspect of the present invention is to provide systems and methods that improve the accuracy of an assay that comprise at least one or more parameters each having a random error.

Abstract: The present invention is related to, among other things, the devices and methods that improve the accuracy and reliability of an assay, even when the assay device and/or the operation of the assay device has certain errors, and in some embodiments the errors are random.

Abstract: Disclosed is an apparatus and method for imaging: a side-view of a object on a surface, a Contact Angle of a liquid object, the color of an object, or combinations thereof.

Abstract: One aspect of the present invention is to provide systems and methods that improve the accuracy of an assay that comprise at least one or more parameters each having a random error.

Abstract: The present invention is related to correct the errors in instruments, operation, and others using intelligent monitoring structures and machine learning, and others.

Abstract: The present invention is related to correct the errors in instruments, operation, and others using intelligent monitoring structures and machine learning, and others.

Abstract: The present invention is related to correct the errors in instruments, operation, and others using intelligent monitoring structures and machine learning, and others.

Abstract: The present invention is related to, among other things, the devices and methods that improve the accuracy and reliability of an assay, even when the assay device and/or the operation of the assay device has certain errors, and in some embodiments the errors are random.

Abstract: One aspect of the present invention is to provide systems and methods that improve the accuracy of an assay that comprise at least one or more parameters each having a random error.

Abstract: Disclosed is an apparatus and method for imaging: a side-view of a object on a surface, a Contact Angle of a liquid object, the color of an object, or combinations thereof.

Abstract: The present invention is related to correct the errors in instruments, operation, and others using intelligent monitoring structures and machine learning, and others.

Abstract: Among other things, the present invention is related to devices/apparatus and methods of performing cellular, biological, and chemical assays and procedures.

Abstract: A method of assaying an analyte in a sample is disclosed. The method includes having a sample holder with a sample contact area for contacting a sample with an analyte, having a plurality of calibration structures on the sample contact area of the sample holder, imaging a part of the sample contact area that has the calibration structures, and using an algorithm that includes an image, calibration structures in the image, and artificial intelligence and/or machine learning to identify the analyte and/or determine the analyte concentration.

Abstract: Methods and systems facilitate efficient and effective special effects in video streaming. In one embodiment, an apparatus enables special effects by decoding video frames in accordance with a decoding process. The decoding process includes: accessing a plurality of streams of video (wherein each stream originates from a respective camera of a camera array) and decoding frames from the plurality of streams of video. A first stream from a first camera comprises: a first primary special effect predictive (SP) frame that is coded based upon a predictive (P) frame in the first stream; and a first secondary special effect predictive (SP) frame that is coded based upon a primary special effect predictive (SP) frame included in a second stream from a second camera. The method further comprises rendering a special effect using the primary and secondary special effect predictive (SP) frames.