Methods, systems and apparatus, including computer programs encoded on computer storage medium, for training a neurosymbolic data imputation system on training data inputs in a domain to impute missing data in a data input from the data domain. In one aspect a method includes, for each training data input, adding random noise to missing fields of the training data input;

generating an embedding data input for the training data input using concept embeddings from the domain; processing the noisy data input and the embedding data input through a correlation network to obtain correlation data; applying attention to the noisy training data input and the correlation data to generate a combined data input; processing, by an autoencoder, the combined data input to obtain a decoded data output; computing a difference between the decoded data output and the training data input; and updating parameters of the data imputation system using the difference.

Systems and computer-implemented methods of performing image registration. One method includes receiving a first image and a second image acquired from a patient at different times and, in each of the first image and the second image, detecting an upper boundary of an imaged object in an image coordinate system and detecting a lower boundary of the imaged object in the image coordinate system. The method further includes, based on the upper boundary and the lower boundary of each of the first image and the second image, cropping and padding at least one of the first image and the second image to create an aligned first image and an aligned second image and executing a registration model on the aligned first image and the aligned second image to compute a deformation field between the aligned first image and the aligned second image.

A method for generating and presenting a patient readmission risk using a readmission risk analysis system, comprising: (i) receiving information about the patient, wherein the information comprises a plurality of readmission prediction features; (ii) extracting the plurality of readmission prediction features from the received information; (iii) analyzing the readmission prediction features to determine whether each of a predetermined list of readmission prediction features are present; (iv) replacing one or more identified missing readmission prediction features with a null value to generate a complete set of readmission prediction features for the patient; (v) analyzing the complete set of readmission prediction features for the patient to generate a readmission risk score; (vi) determining, using a populated lookup table of the readmission risk analysis system, an AUC score; and (vii) displaying the generated readmission risk score and the determined AUC score.

The invention provides systems and methods that stage sleep in patients using wearable devices regardless of the brand or features of the wearable device. Data collected from wearable devices are assigned a sleep stage regardless of manufacture or mode of operation. Methods provide precise and accurate sleep stage information to physicians via an online portal of the system, offering patients suffering from poor sleep opportunities for better medical outcomes. Methods include preprocessing data for a subject from a first sensor on a first wearable device; based on a type of the wearable device into standardized data and analyzing the standardized to identify sleep stages. Second data from a second wearable device with different formats or different content is also preprocessed a format matching that of the standardized data.

The invention provides systems and methods that stage sleep in patients using wearable devices regardless of the brand or features of the wearable device. Data collected from wearable devices are assigned a sleep stage regardless of manufacture or mode of operation. Methods provide precise and accurate sleep stage information to physicians via an online portal of the system, offering patients suffering from poor sleep opportunities for better medical outcomes. Methods include preprocessing data for a subject from a first sensor on a first wearable device; based on a type of the wearable device into standardized data and analyzing the standardized to identify sleep stages. Second data from a second wearable device with different formats or different content is also preprocessed a format matching that of the standardized data.

A system for decision support includes a path unit for determining a determined path through a decision tree that leads to a determined recommendation node including a determined recommendation. The decision tree comprises condition nodes and recommendation nodes, wherein a condition node comprises a condition associated with a particular branch of the decision tree. A recommendation node comprises a recommendation associated with the one or more conditions of the one or more condition nodes on a path towards the recommendation node. The path unit is arranged for taking into account the conditions of the condition nodes along the path by applying the conditions to a set of parameters. The system comprises an explanation unit for generating an explanation of a reason for the determined recommendation based on at least one of the condition nodes on the path that leads to the recommendation node.

A system for decision support includes a path unit for determining a determined path through a decision tree that leads to a determined recommendation node including a determined recommendation. The decision tree comprises condition nodes and recommendation nodes, wherein a condition node comprises a condition associated with a particular branch of the decision tree. A recommendation node comprises a recommendation associated with the one or more conditions of the one or more condition nodes on a path towards the recommendation node. The path unit is arranged for taking into account the conditions of the condition nodes along the path by applying the conditions to a set of parameters. The system comprises an explanation unit for generating an explanation of a reason for the determined recommendation based on at least one of the condition nodes on the path that leads to the recommendation node.

A medical information processing system of an embodiment includes a processing circuit. The processing circuit acquires examination data showing medical examination results with respect to a medical treatment subject and reply data showing reply results of a medical examination by interview with respect to the medical treatment subject. The processing circuit estimates information on medical treatment of the medical treatment subject by inputting the examination data of the medical treatment subject to a first model and estimates information on medical treatment of the medical treatment subject by inputting the examination data and the reply data of the medical treatment subject to a second model. The processing circuit outputs a first estimation result of the first model and a second estimation result of the second model via an output unit.

A medical information processing system of an embodiment includes a processing circuit. The processing circuit acquires examination data showing medical examination results with respect to a medical treatment subject and reply data showing reply results of a medical examination by interview with respect to the medical treatment subject. The processing circuit estimates information on medical treatment of the medical treatment subject by inputting the examination data of the medical treatment subject to a first model and estimates information on medical treatment of the medical treatment subject by inputting the examination data and the reply data of the medical treatment subject to a second model. The processing circuit outputs a first estimation result of the first model and a second estimation result of the second model via an output unit.

A method is provided for lowering blood pressure in a subject in need thereof by administering a dihydropyridine-type calcium channel blocker pharmaceutical composition to a subject qualified for over-the-counter access to the dihydropyridine-type calcium channel blocker pharmaceutical composition. In some embodiments, the dihydropyridine-type calcium channel blocker pharmaceutical composition includes isradipine, nifedipine, or nisoldipine. In some embodiments, the dihydropyridine-type calcium channel blocker pharmaceutical composition includes 3-O-ethyl 5-O-methyl 2-(2-aminoethoxymethyl)-4-(2-chlorophenyl)-6-methyl-1,4-dihydropyridine-3,5-dicarboxylate or a pharmaceutically acceptable salt thereof.