Abstract: Systems, methods, and apparatuses for generating and using machine learning models using genetic data. A set of input features for training the machine learning model can be identified and used to train the model based on training samples, e.g., for which one or more labels are known. As examples, the input features can include aligned variables (e.g., derived from sequences aligned to a population level or individual references) and/or non-aligned variables (e.g., sequence content). The features can be classified into different groups based on the underlying genetic data or intermediate values resulting from a processing of the underlying genetic data. Features can be selected from a feature space for creating a feature vector for training a model. The selection and creation of feature vectors can be performed iteratively to train many models as part of a search for optimal features and an optimal model.

Abstract: A steerable biopsy device comprises an outer sheath comprising a sheath body having a proximal sheath section and a distal sheath section. The outer sheath further comprises a distal sheath tip and a sheath lumen terminating at a distal port in the distal sheath tip. The biopsy device further comprises a biopsy needle integrated with the sheath body. The biopsy needle is slidably disposed in the sheath lumen. The biopsy needle comprises a needle shaft and a distal needle tip configured for being displaced between a stored position within the sheath lumen and a deployed position outside of the distal port of the distal sheath tip. The biopsy device further comprises an articulation control actuator configured for articulating the distal sheath section, and a needle actuator configured for distally advancing the distal needle tip from the stored position to the deployed position.

Abstract: A steerable biopsy device comprises an outer sheath comprising a sheath body having a proximal sheath section and a distal sheath section. The outer sheath further comprises a distal sheath tip and a sheath lumen terminating at a distal port in the distal sheath tip. The biopsy device further comprises a biopsy needle integrated with the sheath body. The biopsy needle is slidably disposed in the sheath lumen. The biopsy needle comprises a needle shaft and a distal needle tip configured for being displaced between a stored position within the sheath lumen and a deployed position outside of the distal port of the distal sheath tip. The biopsy device further comprises an articulation control actuator configured for articulating the distal sheath section, and a needle actuator configured for distally advancing the distal needle tip from the stored position to the deployed position.

Abstract: A steerable biopsy device comprises an outer sheath comprising a sheath body having a proximal sheath section and a distal sheath section. The outer sheath further comprises a distal sheath tip and a sheath lumen terminating at a distal port in the distal sheath tip. The biopsy device further comprises a biopsy needle integrated with the sheath body. The biopsy needle is slidably disposed in the sheath lumen. The biopsy needle comprises a needle shaft and a distal needle tip configured for being displaced between a stored position within the sheath lumen and a deployed position outside of the distal port of the distal sheath tip. The biopsy device further comprises an articulation control actuator configured for articulating the distal sheath section, and a needle actuator configured for distally advancing the distal needle tip from the stored position to the deployed position.

Abstract: Methods, systems, and devices are presented relating to networking through a wireless mesh network. The method comprises pairing a first handheld device with a first machine to machine networking device associated with a first user and pairing a second handheld device with a second machine to machine networking device associated with a second user. The method further comprises matching the first user with at least the second user over a wireless mesh network and communicating the match to at least the first user. The matching of users can involve determining the first and second user have at least one defined preference in common.