GE Precision Healthcare

A maternal-fetal monitoring system comprises at least one physiological sensor configured to obtain at least a first maternal parameter of a maternal patient and at least a first fetal parameter of a first fetal patient. A controller is configured to compare the first fetal parameter to a plurality of fetal alarm thresholds and generate a first fetal alarm for the first fetal patient in response to the first fetal parameter passing a first one of the fetal alarm thresholds, wherein the first fetal alarm includes a first fetal alarm time and a first fetal alarm level. A new fetal alarm is generated each time the first fetal parameter passes one of the plurality of fetal alarm thresholds, wherein each new fetal alarm includes a new fetal alarm time and a new fetal alarm level. A list of fetal alarms is generated for the first fetal patient based on the first fetal alarm and each new fetal alarm.

Various methods and systems are provided for anesthesia systems which may include a cartridge pump assembly including a cartridge containing a liquid anesthetic and a pump adapted to pressurize the liquid anesthetic through a pressure line and a reservoir. An injector may deliver the liquid anesthetic into a heater assembly. The system further includes a liquid flow valve configured to fluidly couple and decouple the cartridge and the injector.

Systems and methods are provided for calibrating a computed tomography (CT) system (100) using a wire phantom (302) coupled to a table of the CT system (100), where during a calibration of the CT system (100), a position of a detector element (202) of a detector array of the CT system (100) is measured using a wire (304) of the wire phantom (302), during a rotational scan performed using the CT system (100). During a subsequent scan, the measured position of the detector element (202) may be applied during reconstruction of an image from projection data acquired via the CT system (100). The method relies on a straightness of the wire (304) within the wire phantom (302), which is maintained by spherical swage-end terminations (1012, 1014) of the wire (304) when tension is applied to the wire (304) A phantom holder (323) of the wire phantom (302) may include a clamp (1701) and a handle (2002) for positioning the wire phantom (302) on the table.

A system for training on infant care devices includes a processor and a memory. The memory includes instructions executable by the processor to receive a request for training on an infant care device, determine a training selection based on the request, and provide a training based on the training selection, a software application running on the infant care device, and a current user interface being provided by the software application.

A method for multi-analyte recovery from a single tissue sample includes lysing a tissue sample in a lysis buffer. The method also includes adding protamine conjugates (10) including protamine conjugated to a solid support matrix (14) to a lysate of the lysed tissue sample. The method further includes incubating the lysate in the presence of the protamine conjugates (10) in a binding buffer in a reaction mixture to bind nucleic acid to the protamine conjugates (10). The method even further includes removing a supernatant from the reaction mixture containing intact protein and metabolites. The method further includes eluting the nucleic acid from the protamine conjugates (10).

A radiation imaging apparatus includes a substrate (92) and a radiation-sensitive imaging region (96) in the substrate (92) including a plurality of pixels (93) disposed on a surface of the substrate (92), wherein each pixel (93) is configured to act as a detector element. The radiation imaging apparatus also includes a guard region (94) disposed on the surface and including a plurality of guard rings (101) disposed about a periphery of the radiation-sensitive imaging region (96) at or immediately adjacent a cut edge (95) of the substrate (92), wherein the guard region (94) forms an inactive region (98) about the periphery of the radiation-sensitive imaging region (96), and the guard region (94) includes at least one trench (110) formed in the guard region (94) disposed about the periphery of the radiation-sensitive imaging region (96), and wherein the at least one trench (110) is configured to improve detection efficiency of pixels (93) of the plurality of pixels (93) located closest to the cut edge (95) while reducing a width (108) of the guard region (94).

Techniques for estimating target radiation doses for medical imaging exams leveraging artificial intelligence (AI) are described. In an example, a method can comprise training an AI model to estimate target dose information for past medical imaging exams using historical exam reports for the past imaging exams and actual radiation dose information included in the historical exam reports indicating actual radiation dosages exposed to past patients as a result of the past imaging exams. Once trained, the AI model is applied to estimate the target dose information for new medical imaging exams prior to performance of the new exams. The target dose information is further provided to the corresponding imaging systems scheduled for the new exams. In some implementations, the target dose information can control the acquisition protocol used for the exams to ensure compliance with the target dose information.

Embodiments of the present disclosure relate to a positioner system for use with an ultrasound probe to treat a subject via neuromodulation, and the techniques for using the same. In certain embodiments, the positioner system may include a receptacle for receiving the ultrasound probe, a pressure applicator to apply a steady pressure to maintain a position of ultrasound probe against the patient's skin, and a slider arm to extend near or above the subject and support the pressure applicator and probe holder. The positioner system may include multiple degrees of freedom to accommodate a subject's clinical needs and/or treatment protocol that utilizes the ultrasound probe.

Some embodiments of the present disclosure include a processor and a memory. The memory includes instructions executable by the processor to receive training data having vitals scores for pre-term infants indicating a healthiness of a pre-term infant having specific vitals measurements. Further, the instructions are executable to receive training data having maternal health parameters and pregnancy parameters for pregnant women that gave birth to pre-term infants. Additionally, the instructions are executable to receive training data having pre-term infant health parameters and birth parameters for the pre-term infants. Further, the instructions are executable to train an artificial intelligence model to infer a viability score by using the maternal parameters training data, pre-term parameters training data, pre-term vitals training data, and supervised learning. Additionally, the viability score indicates a likelihood of survival for a pre-term infant having a vitals score, maternal parameters, and pre-term parameters.

A neonatal care system includes a processor and a memory. The memory includes instructions configured to cause the processor to receive strain amounts corresponding the strain sensors of a tactile sensor array. Additionally, the instructions cause the processor to generate a strain map comprising a visualization of the strain amounts in association with the corresponding X, Y coordinate locations of the strain sensors. Further, the instructions cause the processor to generate a weight map based on the strain map and a strain-weight model. Additionally, the weight map includes weights corresponding to the strain amounts. Further, the instructions cause the processor to identify a patient location. Additionally, the instructions cause the processor to determine a weight of the patient based on the patient location and the weight map