According to one aspect of the present disclosure, there is provided a method of estimating biometric information about a head using a machine learning, the method including: acquiring an analysis target optical signal detected from a head portion of a person to be measured by at least one optical sensor disposed on the head portion of the person to be measured; and estimating the biometric information about the head of the person to be measured by analyzing the acquired analysis target optical signal using an estimation model learned based on data about an anatomical structure of at least one head portion, data about a biometrical state of the at least one head portion, and data about an optical signal associated with the data about the anatomical structure of at least one head portion and the data about the biometrical state of the at least one head portion.

A computing device for diffusion dictionary imaging (DDI) of microstructure and inflammation of a patient is provided. The DDI computing device is connected to other computing devices, such as a magnetic resonance imaging (MRI) scanner. The DDI computing device receives magnetic resonance (MR) signals from the MRI scanner. Once received, the DDI computing device records the one or more MR signals to a memory device. The DDI computing device computationally processes the one or more MR signals to reconstruct a diffusion MRI image using diffusion dictionary data. The MR signals include values that are used as input to algorithms of the DDI data to reconstruct the diffusion MRI image. A database is used to store DDI data, artificial intelligence (AI) data, diffusion dictionary data, and MR data.

An exemplary hearing device configured to be worn by a user includes a microphone and a processor. The microphone detects an audio signal. The processor is configured to determine that the audio signal includes own voice content representative of a voice of the user and determine that an environmental noise level within the audio signal is below a threshold The processor is further configured to apply, based on the environmental noise level being below the threshold, a biomarker feature analysis heuristic to the own voice content.

A visual perception function evaluation system 10 includes: a display device 12 configured to three-dimensionally display a three-dimensional test image 20 including an object 22 to a subject; a processing device 13 connected to the display device 12; and an input device 11 through which a reply related to whether the object 22 can be perceived is input from the subject to the processing device 13. The processing device 13 includes a display control means 15 for controlling the state of display of the test image 20 on the display device 12, and a neglect region specifying means 16 for specifying a neglect region in a three-dimensional space based on the reply. The display control means 15 controls display so that the three-dimensional position of a display point P varies over time. The neglect region specifying means 16 determines three-dimensional position information on a boundary part between a perception region and the neglect region based on a position of the display point P where it is replied that the object 22 cannot be perceived and an adjacent position of the display point P where it is replied that the object 22 can be perceived.

Disclosed is a method for predicting disease based on a medical image performed by a computing device. The method includes: generating a feature vector related to predictive values of brain disease for each of 2D medical images included in a 3D medical image, using a pre-trained first model; estimating importance indicating prediction accuracy for each of the 2D medical images based on the feature vector, using a pre-trained second model; and selecting at least one model input image suitable for prediction of the brain disease from among the 2D medical images based on the importance.

Systems and methods for the evaluation of clinical treatment efficacy is disclosed. The systems and methods include protocols for selection of appropriate patients/subjects for the evaluation of a specific clinical treatment. The systems and methods are based on objective measures of brain activity. The clinical treatments include pharmacological compounds in development or existing compounds approved by the appropriate regulatory authority (e.g., U.S. Federal Drug Administration), as well as transcranial magnetic or electric stimulation, including non-invasive approaches as well as grid- or depth-based electrode arrays, as well as behavioral therapies.

A method and system for clustering users using cognitive stress report for classifying stress levels is provided. Detection and monitoring of cognitive stress experienced by users while performing a task is very crucial. The method includes receiving, user evaluated cognitive stress reports and the physiological signals of the user during the performance of the task. A normalized cognitive report is generated from the user evaluated cognitive stress report by computing mode and range value. The normalized cognitive stress reports of the users are used to cluster the users into a primary cluster and a secondary cluster. Feature sets are extracted from the physiological signals of the said users associated with the primary cluster. Using the said feature sets a classifier model is trained to classify the cognitive stress levels of the users as stressful class or stressless class.

A medical image diagnosis apparatus according to an embodiment includes an imager, a storage, and processing circuitry. The storage stores therein a correspondence relationship between each of disease patterns and scans used for performing a differential diagnosis process on the disease pattern. The processing circuitry obtains, based on image data acquired by a first scan, a disease pattern having a possibility of being applicable to the subject and a first index value indicating a degree of applicability of the disease pattern. The processing circuitry outputs information indicating the disease pattern to a display when it is possible to perform the differential diagnosis process based on the first index value and outputs an imaging condition used for performing a second scan based on the correspondence relationship and the disease pattern having the possibility when it is not possible to perform the differential diagnosis process based on the first index value.

Provided herein are devices (e.g., electrochemical sensors useful for detecting volatile organic compounds associated with certain diseases or conditions and/or diagnosing certain diseases or conditions). The devices comprise one or more layers of metal on a layer of silicon, and a layer of molecularly imprinted polymer in electrical communication with the one or more layers of metal, wherein the one or more layers of metal are each independently selected from a layer of chromium, platinum, gold, nickel, cobalt, tungsten, rhodium, iridium, silver, tin, titanium or tantalum, or an alloy thereof. Methods of using the devices (e.g., to detect one or more analytes in a sample, to detect and/or diagnose a disease or condition in a subject), and methods of making the devices are also provided.

A method, a computer implemented method, and a device, all for adaptively testing a subjects neurological state. The method comprising the steps of: administering one or more seed questions; obtaining one or more answer(s) to the one or more seed questions; calculating a score value of a latent subject trait from the answers to the one or more seed questions; the method comprising an adaptive test loop, comprising: (a) selecting, based on the score value, one or more further questions from a bank of questions; (b) administering the one or more further questions to the subject; (c) updating the score value based on the answers to the one or more further questions; (d) determining whether a test completion criteria has been met; wherein the method repeats steps (a)-(d) in sequence until the test completion criteria has been met, and provides an output of the test based on the score value which is indicative of the subjects neurological state.