Abstract: Robotic systems can be capable of collision detection and avoidance. A robotic medical system can include a robotic arm, an input device configured to receive one or more user inputs for controlling the robotic arm, and a display configured to provide information related to the robotic medical system. The display can include a first icon that is representative of the robotic arm and includes at least a first state and a second state. The robotic medical system can be configured to control movement of the robotic arm based on the user inputs received at the input device in real time, determine a distance between the robotic arm and a component, and provide information to the user about potential, near, and/or actual collisions between the arm and the component.

Abstract: Systems and methods for implementing machine-learning models for ovarian stimulation is described herein. In some variations, a computer-implemented method may include optimizing an ovarian stimulation process may include receiving patient-specific data associated with a patient, and predicting an egg outcome for the patient for each of a plurality of treatment options for an ovarian stimulation process based on at least one predictive model and the patient-specific data, where the at least one predictive model is trained using prior patient-specific data associated with a plurality of prior patients.

Abstract: Systems and methods for predicting viability of one or more embryos is described herein. In some variations, a method may include receiving a single image of the embryo via a real-time communication link with an image capturing device and generating a viability score for the embryo by classifying the single image via at least one convolutional neural network. In some variations, a method may include receiving a plurality of single images, where each single image depicts a different respective embryo of a plurality of embryos, generating a viability score for each embryo by classifying each single image via at least one convolutional neural network, and ranking the plurality of embryos based on the viability scores for the plurality of embryos.

Abstract: Systems and methods for implementing machine-learning models for ovarian stimulation is described herein. In some variations, a computer-implemented method may include optimizing an ovarian stimulation process may include receiving patient-specific data associated with a patient, and predicting an egg outcome for the patient for each of a plurality of treatment options for an ovarian stimulation process based on at least one predictive model and the patient-specific data, where the at least one predictive model is trained using prior patient-specific data associated with a plurality of prior patients.

Abstract: The systems and methods disclosed herein are directed to robotically controlling a medical device to utilize manual skills and techniques developed by surgeons. The system can include an emulator representing a medical device. The system can include at least one detector configured to track the emulator. The system can also include an imaging device configured to track the medical device. The system may be configured to move the medical device to reduce an alignment offset between the location of the emulator and the location of the medical device, to move the imaging device based on the translational movement of the emulator, and/or to move the medical device based on data indicative of an orientation of the emulator.

Abstract: A robotic system includes control circuitry configured to cause actuation of one or more actuators of each of a first robotic arm and a second robotic arm. The control circuitry is configured to determine a position of a first end effector of the first robotic arm and a position of a second end effector of the second robotic arm, the positions of the first end effector and the second end effector forming a virtual rail, receive manual positioning input for the first robotic arm based at least in part on sensor signals from one or more sensors of the first robotic arm, and in response to the manual positioning input, generate a first movement command to move the first robotic arm in accordance with the manual positioning input and generate a second movement command to move the second robotic arm in a manner as to maintain at least one of a position or orientation of the second end effector relative to a point on the virtual rail.

Abstract: Systems and methods for moving or manipulating robotic arms are provided. A group of robotic arms are configured to form a virtual rail or line between the end effectors of the robotic arms. The robotic arms are responsive to outside force such as from a user. When a user moves a single one of the robotic arms, the other robotic arms will automatically move to maintain the virtual rail alignments. The virtual rail of the robotic arm end effectors may be translated in one or more of three dimensions. The virtual rail may be rotated about a point on the virtual rail line. The robotic arms can detect the nature of the contact from the user and move accordingly. Holding, shaking, tapping, pushing, pulling, and rotating different parts of the robotic arm elicits different movement responses from different parts of the robotic arm.

Abstract: Systems and methods for implementing machine-learning models for ovarian stimulation is described herein. In some variations, a computer-implemented method may include optimizing an ovarian stimulation process may include receiving patient-specific data associated with a patient, and predicting an egg outcome for the patient for each of a plurality of treatment options for an ovarian stimulation process based on at least one predictive model and the patient-specific data, where the at least one predictive model is trained using prior patient-specific data associated with a plurality of prior patients.

Abstract: Robotic systems can be capable of collision detection and avoidance. A robotic medical system can include a robotic arm, an input device configured to receive one or more user inputs for controlling the robotic arm, and a display configured to provide information related to the robotic medical system. The display can include a first icon that is representative of the robotic arm and includes at least a first state and a second state. The robotic medical system can be configured to control movement of the robotic arm based on the user inputs received at the input device in real time, determine a distance between the robotic arm and a component, and provide information to the user about potential, near, and/or actual collisions between the arm and the component.

Abstract: Certain aspects relate to admittance control modes for a robotic surgery system. The admittance control modes can be based on detecting and/or measuring forces (rotational and/or nonrotational) on a robotic arm and moving the robotic arm in response to such interactions. The forces can include direct manual interaction with the robotic arm by a clinician. The movement of the robotic arm can be within a nullspace that maintains the positions of a medical instrument.

Abstract: The systems and methods disclosed herein are directed to robotically controlling a medical device to utilize manual skills and techniques developed by surgeons. The system can include an emulator representing a medical device. The system can include at least one detector configured to track the emulator. The system can also include an imaging device configured to track the medical device. The system may be configured to move the medical device to reduce an alignment offset between the location of the emulator and the location of the medical device, to move the imaging device based on the translational movement of the emulator, and/or to move the medical device based on data indicative of an orientation of the emulator.

Abstract: The systems and methods disclosed herein are directed to robotically controlling a medical device to utilize manual skills and techniques developed by surgeons. The system may comprise an emulator representing a medical device. The system may comprise at least one detector configured to track the emulator. The system may further comprise an imaging device configured to track the medical device. The system may be configured to move the medical device to reduce an alignment offset between the location of the emulator and the location of the medical device, to move the imaging device based on the translational movement of the emulator, and/or to move the medical device based on data indicative of an orientation of the emulator.

Abstract: Systems and methods for moving or manipulating robotic arms are provided. A group of robotic arms are configured to form a virtual rail or line between the end effectors of the robotic arms. The robotic arms are responsive to outside force such as from a user. When a user moves a single one of the robotic arms, the other robotic arms will automatically move to maintain the virtual rail alignments. The virtual rail of the robotic arm end effectors may be translated in one or more of three dimensions. The virtual rail may be rotated about a point on the virtual rail line. The robotic arms can detect the nature of the contact from the user and move accordingly. Holding, shaking, tapping, pushing, pulling, and rotating different parts of the robotic arm elicits different movement responses from different parts of the robotic arm.

Abstract: Systems and methods for moving or manipulating robotic arms are provided. A group of robotic arms are configured to form a virtual rail or line between the end effectors of the robotic arms. The robotic arms are responsive to outside force such as from a user. When a user moves a single one of the robotic arms, the other robotic arms will automatically move to maintain the virtual rail alignments. The virtual rail of the robotic arm end effectors may be translated in one or more of three dimensions. The virtual rail may be rotated about a point on the virtual rail line. The robotic arms can detect the nature of the contact from the user and move accordingly. Holding, shaking, tapping, pushing, pulling, and rotating different parts of the robotic arm elicits different movement responses from different parts of the robotic arm.

Abstract: The systems and methods disclosed herein are directed to robotically controlling a medical device to utilize manual skills and techniques developed by surgeons. The system may comprise an emulator representing a medical device. The system may comprise at least one detector configured to track the emulator. The system may further comprise an imaging device configured to track the medical device. The system may be configured to move the medical device to reduce an alignment offset between the location of the emulator and the location of the medical device, to move the imaging device based on the translational movement of the emulator, and/or to move the medical device based on data indicative of an orientation of the emulator.

Abstract: Systems and methods for moving or manipulating robotic arms are provided. A group of robotic arms are configured to form a virtual rail or line between the end effectors of the robotic arms. The robotic arms are responsive to outside force such as from a user. When a user moves a single one of the robotic arms, the other robotic arms will automatically move to maintain the virtual rail alignments. The virtual rail of the robotic arm end effectors may be translated in one or more of three dimensions. The virtual rail may be rotated about a point on the virtual rail line. The robotic arms can detect the nature of the contact from the user and move accordingly. Holding, shaking, tapping, pushing, pulling, and rotating different parts of the robotic arm elicits different movement responses from different parts of the robotic arm.

Abstract: Systems and methods for moving or manipulating robotic arms are provided. A group of robotic arms are configured to form a virtual rail or line between the end effectors of the robotic arms. The robotic arms are responsive to outside force such as from a user. When a user moves a single one of the robotic arms, the other robotic arms will automatically move to maintain the virtual rail alignments. The virtual rail of the robotic arm end effectors may be translated in one or more of three dimensions. The virtual rail may be rotated about a point on the virtual rail line. The robotic arms can detect the nature of the contact from the user and move accordingly. Holding, shaking, tapping, pushing, pulling, and rotating different parts of the robotic arm elicits different movement responses from different parts of the robotic arm.

Abstract: Systems and methods for moving or manipulating robotic arms are provided. A group of robotic arms are configured to form a virtual rail or line between the end effectors of the robotic arms. The robotic arms are responsive to outside force such as from a user. When a user moves a single one of the robotic arms, the other robotic arms will automatically move to maintain the virtual rail alignments. The virtual rail of the robotic arm end effectors may be translated in one or more of three dimensions. The virtual rail may be rotated about a point on the virtual rail line. The robotic arms can detect the nature of the contact from the user and move accordingly. Holding, shaking, tapping, pushing, pulling, and rotating different parts of the robotic arm elicits different movement responses from different parts of the robotic arm.