Abstract: Method of haplotype analysis. In an exemplary method, an aqueous phase containing nucleic acid may be partitioned into a plurality of discrete volumes. At least one allele sequence may be amplified in the volumes from each of a first polymorphic locus and a second polymorphic locus that exhibit sequence variation in the nucleic acid. At least one measure of co-amplification of allele sequences from both loci in the same volumes may be determined. A haplotype of the first and second loci may be selected based on the at least one measure of co-amplification.

Abstract: Embodiments described herein provide for training an artificial intelligence model to become a preference-aware model. The artificial intelligence model preferences as the artificial intelligence model trains. Reinforcement learning is used to train experts in the artificial intelligence model such that each expert is trained to converge to a unique preference. The architecture of the artificial intelligence model is highly flexible. Upon executing a trained model, users can select automatically images according to various preferences based on medical professional preferences, geographic preferences, patient anatomy, and institutional guidelines.

Abstract: Method of haplotype analysis. In an exemplary method, an aqueous phase containing nucleic acid may be partitioned into a plurality of discrete volumes. At least one allele sequence may be amplified in the volumes from each of a first polymorphic locus and a second polymorphic locus that exhibit sequence variation in the nucleic acid. At least one measure of co-amplification of allele sequences from both loci in the same volumes may be determined. A haplotype of the first and second loci may be selected based on the at least one measure of co-amplification.

Abstract: A system for building a product library without requiring a planogram includes an image capture unit operated to provide images of items. Taking data from a shelf label detector and depth map creation unit, a processing module can be used to compare detected shelf labels to a depth map, define a product bounding box, and associate the bounding box with an image provided by the image capture unit to build image descriptors. The system can include one or more autonomous robots for supporting and moving the image capture unit and other components.

Abstract: An object recognition system can be adapted to recognize subject matter having very few features or limited or no texture. A feature-sparse or texture-limited object can be recognized by complementing local features and/or texture features with color, region-based, shape-based, three-dimensional (3D), global, and/or composite features. Machine learning algorithms can be used to classify such objects, and image matching and verification can be adapted to the classification. Further, multiple modes of input can be integrated at various stages of the object recognition processing pipeline. These multi-modal inputs can include user feedback, additional images representing different perspectives of the object or specific regions of the object including a logo or text corresponding to the object, user behavior data, location, among others.

Abstract: A manually assisted robot inventory monitoring method provides for detecting and reading shelf labels using an autonomous robot. Bounding boxes around possible products in a panoramic image can be taken with at least one camera associated with the autonomous robot. Products in the bounding boxes are automatically identified, with those that are not being later manually identified.

Abstract: Method of haplotype analysis. In an exemplary method, an aqueous phase containing nucleic acid may be partitioned into a plurality of discrete volumes. At least one allele sequence may be amplified in the volumes from each of a first polymorphic locus and a second polymorphic locus that exhibit sequence variation in the nucleic acid. At least one measure of co-amplification of allele sequences from both loci in the same volumes may be determined. A haplotype of the first and second loci may be selected based on the at least one measure of co-amplification.

Abstract: Provided herein are improved methods, compositions, and kits for analysis of nucleic acids. The improved methods, compositions, and kits can enable copy number estimation of a nucleic acid in a sample. Also provided herein are methods, compositions, and kits for determining the linkage of two or more copies of a target nucleic acid in a sample (e.g. whether the two or more copies are on the same chromosome or different chromosomes) or for phasing alleles.

Abstract: Various embodiments may increase scalability of image representations stored in a database for use in image matching and retrieval. For example, a system providing image matching can obtain images of a number of inventory items, extract features from each image using a feature extraction algorithm, and transform the same into their feature descriptor representations. These feature descriptor representations can be subsequently stored and used to compare against query images submitted by users. Though the size of each feature descriptor representation isn't particularly large, the total number of these descriptors requires a substantial amount of storage space. Accordingly, feature descriptor representations are compressed to minimize storage and, in one example, machine learning can be used to compensate for information lost as a result of the compression.

Abstract: System, including methods and apparatus, for performing a multiplexed digital assay.

Abstract: A system for building a product library without requiring a planogram includes an image capture unit operated to provide images of items. Taking data from a shelf label detector and depth map creation unit, a processing module can be used to compare detected shelf labels to a depth map, define a product bounding box, and associate the bounding box with an image provided by the image capture unit to build image descriptors. The system can include one or more autonomous robots for supporting and moving the image capture unit and other components.

Abstract: A manually assisted robot inventory monitoring method provides for detecting and reading shelf labels using an autonomous robot. Bounding boxes around possible products in a panoramic image can be taken with at least one camera associated with the autonomous robot. Products in the bounding boxes are automatically identified, with those that are not being later manually identified.

Abstract: An object recognition system can be adapted to recognize subject matter having very few features or limited or no texture. A feature-sparse or texture-limited object can be recognized by complementing local features and/or texture features with color, region-based, shape-based, three-dimensional (3D), global, and/or composite features. Machine learning algorithms can be used to classify such objects, and image matching and verification can be adapted to the classification. Further, multiple modes of input can be integrated at various stages of the object recognition processing pipeline. These multi-modal inputs can include user feedback, additional images representing different perspectives of the object or specific regions of the object including a logo or text corresponding to the object, user behavior data, location, among others.

Abstract: An object recognition system can be adapted to recognize subject matter having very few features or limited or no texture. A feature-sparse or texture-limited object can be recognized by complementing local features and/or texture features with color, region-based, shape-based, three-dimensional (3D), global, and/or composite features. Machine learning algorithms can be used to classify such objects, and image matching and verification can be adapted to the classification. Further, multiple modes of input can be integrated at various stages of the object recognition processing pipeline. These multi-modal inputs can include user feedback, additional images representing different perspectives of the object or specific regions of the object including a logo or text corresponding to the object, user behavior data, location, among others.

Abstract: System, including methods and apparatus, for performing a multiplexed digital assay.

Abstract: Various embodiments may increase scalability of image representations stored in a database for use in image matching and retrieval. For example, a system providing image matching can obtain images of a number of inventory items, extract features from each image using a feature extraction algorithm, and transform the same into their feature descriptor representations. These feature descriptor representations can be subsequently stored and used to compare against query images submitted by users. Though the size of each feature descriptor representation isn't particularly large, the total number of these descriptors requires a substantial amount of storage space. Accordingly, feature descriptor representations are compressed to minimize storage and, in one example, machine learning can be used to compensate for information lost as a result of the compression.

Abstract: Various embodiments of the disclosed subject matter include computer-implemented methods, computer-readable media, and computer systems configured to respond to a search query from a computer user. In response to receiving a search query from the computer user, search results are obtained. A plurality of user intents are identified according to the obtained search results. The obtained search results are then grouped according to the subject matter of the search results, where each group corresponds to one of the plurality of user intents. A first user intent (with the corresponding group of search results) is selected. A search results page is generated from the search results of the group the search results corresponding to the selected first user intent and the generated search results page is returned to the computer user in response to the search query.

Abstract: Various embodiments may increase scalability of image representations stored in a database for use in image matching and retrieval. For example, a system providing image matching can obtain images of a number of inventory items, extract features from each image using a feature extraction algorithm, and transform the same into their feature descriptor representations. These feature descriptor representations can be subsequently stored and used to compare against query images submitted by users. Though the size of each feature descriptor representation isn't particularly large, the total number of these descriptors requires a substantial amount of storage space. Accordingly, feature descriptor representations are compressed to minimize storage and, in one example, machine learning can be used to compensate for information lost as a result of the compression.

Abstract: Various embodiments of the disclosed subject matter include computer-implemented methods, computer-readable media, and computer systems configured to respond to a search query from a computer user. In response to receiving a search query from the computer user, search results are obtained. A plurality of user intents are identified according to the obtained search results. The obtained search results are then grouped according to the subject matter of the search results, where each group corresponds to one of the plurality of user intents. A first user intent (with the corresponding group of search results) is selected. A search results page is generated from the search results of the group the search results corresponding to the selected first user intent and the generated search results page is returned to the computer user in response to the search query.

Abstract: A method of estimating a concentration of DNA molecules in a biological sample includes storing a number of a plurality of reaction sites in a memory and distributing the biological sample among the plurality of reaction sites. The method also includes determining a number of the plurality of reaction sites characterized by a presence of one or more of the DNA molecules and computing a portion of the plurality of reaction sites characterized by the presence of the one or more of the DNA molecules. The method further includes estimating the concentration of the DNA molecules as a function of the portion of the plurality of reaction sites and computing a confidence interval for the estimated concentration of DNA molecules.