A biological function estimation device includes a processor configured to predict a drug reaction in a patient based on an evaluation value obtained by evaluating a biological function of the patient from a test result before drug administration and data on a drug to be administered to the patient, and configured to correct the evaluation value according to a comparison result between an obtained prediction value and a measurement value obtained by measuring the drug reaction after the drug administration.

Embodiments herein relate to devices and methods for assessing pulmonary status using optical oxygenation sensing. In an embodiment, an oxygenation monitoring device can be included having a first optical emitter, wherein the first optical emitter can be configured to emit light at a first wavelength from 100 nanometers (nm) to 2000 nm. The oxygenation monitoring device and further include a first optical detector, wherein the first optical detector can be configured to detect incident light. The device can be configured so that emitted light from the first optical emitter propagates through a lung tissue and detected incident light can be used to determine an oxygenation status of the lung tissue. Other embodiments are also included herein.

Embodiments facilitate generation of a prediction of long-term survival (LTS) or short-term survival (STS) of Glioblastoma (GBM) patients. A first set of embodiments discussed herein relates to training of a machine learning classifier to determine a prediction for LTS or STS based on a radiographic-deformation and textural heterogeneity (r-DepTH) descriptor generated based on radiographic images of tissue demonstrating GBM. A second set of embodiments discussed herein relates to determination of a prediction of disease outcome for a GBM patient of LTS or STS based on an r-DepTH descriptor generated based on radiographic imagery of the patient.

Multi-state engagement with continuous glucose monitoring (CGM) systems is described. Given the number of people that wear CGM systems and because CGM systems produce measurements continuously, a platform that provides a CGM system may have an enormous amount of data. This amount of data is practically, if not actually, impossible for humans to process. In implementations, a CGM platform includes a data analytics platform that obtains packages of glucose measurements provided by a CGM system and also obtains additional data associated with a user. The data analytics platform generates state information for the user by processing these CGM packages and the additional data, at least in part, by using one or more models. Based on this state information, the data analytics platform controls communication with the user, which may include generating intervention strategies to prevent users from transitioning to a negative state such as discontinuing use of the CGM system.

The present invention teaches an articular fracture rehabilitation process measuring device. The measuring device comprises a base plate, a positioning tube, and an electronic angle gauge; the positioning tube and the electronic angle gauge are fixed separately on the base plate. The electronic angle gauge comprises a distance sensor, a rotation angle sensor, a data processor, and a digital display; the data processor is connected to the distance sensor and the rotation angle sensor; the digital display is connected with the data processor.

A method for determining an efficacy of medication treatment for a patient includes determining, by one or more processors, based on a local field potential (LFP) activity of the patient, when the patient takes medication and/or a duration of when the medication is effective. The method further includes outputting, by the one or more processors, an indication of when the patient takes the medication and/or the duration of when the medication is effective to facilitate a treatment for the patient.

A wearable treatment and analysis module is provided. The module is positioned on or near a body surface region of interest. The module provides remote access to sensor data, treatment administration, and/or other health care regimens via a network connection with a user device and/or management system.

The disclosure provides a comprehensive limbal stem cell deficiency diagnostic and staging system that combines observations of physiological parameters such as clinical presentation, central cornea basal cell density, central corneal epithelial thickness, and total corneal nerve fiber length. It has been discovered that the methodology disclosed herein can both accurately and objectively diagnose limbal stem cell deficiency as well as stage its severity.

The present invention relates to a device and a method for detecting a peak of an intracranial pressure (ICP) waveform using a morphological feature of an arterial blood pressure waveform. A peak extracting method of an ICP waveform using a morphological feature of an arterial blood pressure waveform according to an aspect of the present invention includes: extracting a pulse onset from a continuous ICP waveform based on systolic peak from arterial blood pressure waveform; dividing individual ICP waveforms in the continuous ICP waveform based on the pulse onset; deriving a derivative value from each of the ICP waveforms to extract a peak, a trough, and a flat; calculating latencies from the pulse onset extracted in each of the ICP waveforms to the extracted peaks to cluster peaks with a similar time interval and generate a peak cluster; searching a notch from each of the ICP waveforms based on the latency of a dicrotic notch of the arterial blood pressure waveform; and extracting P1, P2, and P3 peaks from each of the ICP waveforms by referring to the searched notch of the ICP.

Antibody formulations and methods useful for treatment of patients with AL amyloidosis.