In some aspects, the described systems and methods provide for a method comprising transmitting to a skull of a patient, with at least one transducer, acoustic signals. The method further comprises receiving from the skull, with the at least one transducer, data acquired from the skull including information related to guided waves, distribution of acoustic modes, frequency response, and/or impulse/transient response. The method further comprises determining, from the acquired data, intracranial pressure of the person.

In some aspects, the described systems and methods provide for a method comprising transmitting, with at least one transducer, acoustic signals to a brain of a patient, wherein the at least one transducer is configured to induce excitation of a plurality of acoustic modes. The method further comprises receiving, with the at least one transducer, data acquired from the brain including information related to standing waves, frequency response, impulse/transient response, and/or distribution of acoustic modes. The method further comprises determining, from the acquired data, a distribution of intracranial pressure within the brain of the person.

In some aspects, the described systems and methods provide for a method comprising transmitting to a brain of a patient, with at least one transducer, acoustic signals. The method further comprises receiving from the brain, with the at least one transducer, data acquired from the brain including information related to standing waves, distribution of acoustic modes, frequency response, and/or impulse/transient response. The method further comprises detecting, from the acquired data, a seizure of the person.

In some aspects, the described systems and methods provide for a method comprising transmitting to a brain and/or skull of a patient, with at least one transducer, acoustic signals. The method further comprises receiving from the brain and/or skull, with the at least one transducer, data acquired from the brain and/or skull including information related to standing waves, guided waves, distribution of acoustic modes, frequency response, and/or impulse/transient response. The method further comprises determining, from the acquired data, presence of a tumor within the brain of the person.

In some aspects, the described systems and methods provide for a method comprising transmitting, with at least one transducer, acoustic signals to a brain of a patient, wherein the at least one transducer is configured to induce excitation of a plurality of acoustic modes. The method further comprises receiving, with the at least one transducer, data acquired from the brain including information related to standing waves, frequency response, impulse/transient response, and/or distribution of acoustic modes. The method further comprises determining, from the acquired data, a location of a seizure site within the brain of the person.

A decision support tool is provided for discharging a patient by predicting the probability of a patient's readmission with pneumonia based on information available prior to discharge. The information used to make the prediction may include labs, vitals, diagnoses, and medications from prior encounters and from the current encounter. At least some of this information may be used to compute one or more severity metrics for the patient, such as a cancer score, an epilepsy or seizure score, a pneumococcal pneumonia score, and an instability score, to be input into one or more prediction models. An ensemble of machine learning models may be applied to the patient information to generate a prediction of that patient being readmitted with pneumonia within a future time interval. Based on the prediction, one or more intervening actions may be initiated to reduce the probability of readmission.

Described are methods, devices, and systems for a novel, inexpensive, easy to use therapy for treatment of anxiety. Described are methods and devices to treat anxiety that involves no medication. Methods and devices described herein use alternating magnetic fields to gently tune the brain and affect symptoms of anxiety.

An implantable medical device includes a detecting unit, a control unit and a communication unit. The control unit uses a seizure prediction algorithm to predict epilepsy seizure events in real time based on physiological information detected by the detecting unit, and stores internal data which comprise the detected physiological information and prediction information about the prediction result. The control unit is configured to, in a first communication mode, control its memory unit and communication unit to transmit the internal data to the external monitoring device, and in a second communication mode, control the communication unit to receive an updated seizure prediction algorithm from the external monitoring device and stores the algorithm in the memory unit for predicting seizure events.

There is provided a system and method for interfacing with biological tissue. The system includes: a feature extraction module to implement an extraction approach to extract one or more features from the one or more physiological recording signals; a machine learning module to apply a machine learning model based on input data to detect a physiological event or condition for classification, the input data including the extracted features, the machine learning model trained using a training set including feature vectors of time-series data labelled with known occurrences of the physiological event or condition; and an output module to output the classification of the machine learning module.

Techniques for determining treatment of a subject with IS based on EEG-derived biomarkers are provided. According to some aspects, a method of adapting treatment of a subject having infantile spasms (IS) is provided, the method comprising obtaining electroencephalogram (EEG) data of the subject, determining a measure of delta power of the EEG data and/or a measure of spike frequency of the EEG data, and determining subsequent treatment of the infantile spasms of the subject based at least in part on the determined measure of delta power of the EEG data and/or measure of spike frequency of the EEG data.