An infusion pump system is disclosed. The infusion pump system includes an infusion pump and a controller device in wireless communication with the infusion pump, wherein the controller including instructions for controlling the infusion pump, wherein the instructions may be synchronized with a secure web portal.

The present invention relates to methods for evaluating and/or predicting the outcome of a clinical condition, such as cancer, metastasis, AIDS, autism, Alzheimer's, and/or Parkinson's disorder. The methods can also be used to monitor and track changes in a patient's DNA and/or RNA during and following a clinical treatment regime. The methods may also be used to evaluate protein and/or metabolite levels that correlate with such clinical conditions. The methods are also of use to ascertain the probability outcome for a patient's particular prognosis.

The present invention relates to methods for evaluating the probability that a patient's diagnosis may be treated with a particular clinical regimen or therapy.

Systems and methods for processing sensor data and self-calibration are provided. In some embodiments, systems and methods are provided which are capable of calibrating a continuous analyte sensor based on an initial sensitivity, and then continuously performing self-calibration without using, or with reduced use of, reference measurements. In certain embodiments, a sensitivity of the analyte sensor is determined by applying an estimative algorithm that is a function of certain parameters. Also described herein are systems and methods for determining a property of an analyte sensor using a stimulus signal. The sensor property can be used to compensate sensor data for sensitivity drift, or determine another property associated with the sensor, such as temperature, sensor membrane damage, moisture ingress in sensor electronics, and scaling factors.

A long short-term memory (LSTM) model-based disease prediction method and apparatus, a computer device, and a storage medium are provided. The method includes: obtaining first medical data of a target object and second medical data of an associated object; inputting the first medical data and the second medical data into a first LSTM network in the LSTM model, to obtain a hidden state vector sequence in the first LSTM network; inputting the hidden state vector sequence into a second LSTM network for operation, to obtain a disease prediction result; selecting a predicted disease with an incidence rate higher than a preset threshold, and recording the predicted disease as a designated disease, and obtaining, based on a preset disease association network, an associated disease directly connected to the designated disease; and outputting the disease prediction result and the associated disease, thereby improving the prediction accuracy.

The present solution covers identifying a recommended treatment for a patient based on records of similar patients, wherein the similarities are non-obvious and non-linear. The solution generates a similarity map that minimizes the variance of elements records among a curated group of patients, and this similarity map is used to find the patients who are most similar to an untreated patient.

A tunable implant, system, and method enables a tunable implant to be adjusted within a patient. The tunable implant includes a securing mechanism to secure the implant in the patient, a actuation portion that enables the implant to move and an adjustment portion that permits adjustment of the implant after the implant has been positioned within the patient. The method of adjusting the tunable implant includes analyzing the operation of the implant, determining if any adjustments are necessary and adjusting the implant to improve implant performance. The implant system includes both the tunable implant and a telemetric system that is operable to telemetrically receive data from the tunable implant where the data is used to determine if adjustment of the tunable implant is necessary. The system also includes an instrument assembly that is used for performing spinal surgery where the instrument assembly includes a mounting platform and a jig.

A laser radar device includes: a modulator (8) for causing a transmission seed light beam to branch, and giving different offset frequencies to a plurality of the transmission seed light beams having branched, and then modulating the plurality of transmission seed light beams into pulsed light beams and outputting the pulsed light beams, or for modulating the transmission seed light beam into a pulsed light beam, causing the pulsed light beam to branch, and giving the different offset frequencies to a plurality of the pulsed light beams having branched, and then outputting the plurality of pulsed light beams; a band pass filter (14) in which a frequency band including frequencies of signal components included in a plurality of beat signals detected by an optical heterodyne receiver (13) is set as a pass band and a frequency band not including the frequencies of the signal components is set as a cutoff band; and an ADC (15) for sampling the beat signals passing through the band pass filter (14) at a sampling frequency.

An embodiment of the invention provides a method and system including a sensor on a vehicle and a processor connected to the sensor. The processor determines a probability of falling based on input from the sensor, whether the probability of falling exceeds a threshold, and a state of an operator of the vehicle. An actuator connected to the processor receives a signal from the processor when the probability of falling exceeds the threshold and when the state of the operator includes an impaired state. Stabilizer wheels are connected to the actuator, where the signal includes a command to deploy the stabilizer wheels.

Disclosed herein are assays and methods for the identification of premalignant lesions, as well as methods of determining the likelihood that such premalignant lesions will progress to lung cancer. Also disclosed are methods and assays that are useful for monitoring the progression of premalignant lesions to lung cancer. The assays and methods disclosed herein provide minimally invasive means of accurately detecting and monitoring the presence or absence of premalignant lesions, thus providing novel insights into the earliest stages of lung cancer and facilitating early detection and early intervention.