Abstract: A method for predicting clinical severity of a neurological disorder includes steps of: a) identifying, according to a magnetic resonance imaging (MRI) image of a brain, brain image regions each of which contains a respective portion of diffusion index values of a diffusion index, which results from image processing performed on the MRI image; b) for one of the brain image regions, calculating a characteristic parameter based on the respective portion of the diffusion index values; and c) calculating a severity score that represents the clinical severity of the neurological disorder of the brain based on the characteristic parameter of the one of the brain image regions via a prediction model associated with the neurological disorder.

Abstract: An electronic device and a method for diagnosing heart state based on electrocardiogram (ECG) are provided. An ECG file is obtained, and the ECG file is in a first file format and includes a plurality of potential traces of a plurality of leads. The ECG file is converted to a second file format to obtain electrocardiogram data corresponding to multiple leads. Each potential trace relative to time in the ECG file is converted to the ECG data of each lead. Integrated ECG data associated with the leads is generated based on the ECG data of the plurality of leads through the zero-padding operation and the stacking operation. A diagnostic result of heart status is generated based on the integrated ECG data and a deep learning model.

Abstract: A method includes providing medical images of a subject for selecting a target image from thereamong, building a 3D image model based on the medical images and the target image with a surgical target site assigned, performing image registration to superimpose the 3D image model on a real-time image of the subject so as to result in a combined image, determining a virtual entry site located on the combined image, connecting the surgical target site and the virtual entry site with a straight line, generating a guiding path extending from the virtual entry site, in a direction away from the surgical target site and along the straight line, and displaying the guiding path for guiding a surgical instrument.

Abstract: A construction method of ribosomal RNA database is provided, including the following steps: selecting a source of nucleic acid sequence database; performing normalization and homogenization on species classification rules; using AI technology for normalized classification and correction; selecting the kingdom to which the sequence species belongs; filtering out redundant sequences and sequences with inconsistent lengths; setting a threshold for unknown bases other than A, T, C or G, and excluding unknown bases that exceed the threshold; and excluding sequences with insufficient classification information.

Abstract: A feature selection method is provided, including: inputting a plurality of pieces of training data into a plurality of training models to perform selection in a plurality of features through each training model for obtaining multiple feature pools; sorting the features based on the number of times each feature is selected by the feature pools to obtain a feature ranking; and extracting a plurality of designated features from the features based on the feature ranking.

Abstract: Disclosed herein is a method for diagnosing a neurological disorder based on at least one magnetic resonance imaging (MRI) image. The method includes identifying brain image regions that contain a respective portion of diffusion index values of at least one diffusion index. For each of the brain image regions, a characteristic parameter based on the respective portion of the diffusion index values is calculated. a diagnoses is then made for the brain using one of predetermined categories of the neurological disorder by performing classification on a combination of the characteristic parameters via a classifier.

Abstract: An electronic device and a method for selecting a feature of an electrocardiogram (ECG) are provided. The method includes: obtaining the ECG; performing a first pre-processing on the ECG to generate a first ECG; marking multiple extreme points corresponding to at least one type of wave on the first ECG; calculating a first feature value corresponding to a first feature according to the multiple extreme points of the at least one type of wave, generating a first performance index corresponding to a machine learning model according to the first feature value, and determining whether to select the first feature according to the first performance index; and outputting the first feature in response to selecting the first feature.

Abstract: An electronic device and a method for predicting a blockage of a coronary artery are provided. The method includes: obtaining multiple pieces of electrocardiogram (ECG) data respectively corresponding to a coronary artery set; generating multiple first probabilities corresponding to the multiple pieces of electrocardiogram data respectively according to the multiple pieces of electrocardiogram data and a first phase model, generating a first determined result according to the multiple first probabilities, and selecting a first data subset corresponding to a first probability subset from the multiple pieces of electrocardiogram data in response to each one in the first data subset of the multiple first probabilities being greater than a first threshold; generating multiple second probabilities corresponding to the first data subset according to the first data subset and a second phase model, and generating a second determined result according to the multiple second probabilities.

Abstract: An electronic device and a method for screening features for predicting a physiological state are provided. The method includes: obtaining multiple physiological data corresponding to multiple features; generating multiple first subsets of the multiple features according to the multiple physiological data based on a first model, wherein the multiple first subsets respectively correspond to the multiple physiological data; selecting a first feature from the multiple features according to the multiple first subsets, calculating a first relation index of the first feature and a second feature corresponding to the multiple features, and selecting the second feature as an accompanied feature of the first feature according to the first relation index; and outputting the first feature and the accompanied feature.

Abstract: A method of predicting the risk of a patient for developing phenytoin-induced adverse drug reactions (ADRs), including Stevens-Johnson syndrome (SJS), toxic epidermal necrolysis (TEN), or drug reactions with eosinophilia and systemic symptoms (DRESS) is disclosed. Genetic polymorphisms of CYP2C genes (including rs1057910 (CYP2C9*3) and rs3758581 on CYP2C19), and HLA alleles (including HLA-B*1502, HLA-B*1301, and HLA-B*5101) can predict adverse reactions caused by phenytoin or fosphenytoin. Accordingly, the present invention provides a kit to assess the risk of a patient for developing adverse reactions in response to phenytoin-related drugs, which comprises the determination of the presence of a specific allele selected from the group consisting of rs1057910 (CYP2C9*3), rs3758581 on CYP2C19, HLA-B*1502, HLA-B*1301, and HLA-B*5101, wherein the presence of at least one allele is indicative of a risk for the adverse drug reactions.

Abstract: A method of screening breast cancer includes collecting serum samples from breast cancer patient; measuring WISP1 level in the serum sample; and comparing the serum WISP1 level of the healthy persons with the WISP1 level in the serum sample of the breast cancer patients. The mean serum WISP1 level is 631.5 pg/ml for healthy persons and the mean serum WISP1 level is 934.5 pg/ml for patients having breast cancer so that WISP1 level of 934.5 pg/ml is configured to be a biomarker in determining whether a subject has high risk of breast cancer occurrence or not.

Abstract: The disclosure provides a nutritional composition for improving a patient with heart failure; the nutritional composition is consisting of therapeutically effective high amounts of leucine and histidine. The disclosure also provides the nutritional supplement comprising the nutritional composition, which may be a beverage product, a dietary supplement or food. The disclosure further provides a method of using the nutritional supplement for treating patients with heart failure.

Abstract: The present invention is related to an extracting method of kuguacin, pharmaceutical composition comprising the kuguacin and use thereof, specifically related to a use of the kuguacin for treating periodontal diseases.

Abstract: A method of predicting the risk of a patient for developing phenytoin-induced adverse drug reactions (ADRs), including Stevens-Johnson syndrome (SJS), toxic epidermal necrolysis (TEN), or drug reactions with eosinophilia and systemic symptoms (DRESS) is disclosed. Genetic polymorphisms of CYP2C genes (including CYP2C9, CYP2C19, CYP2C8 and CYP2C18), HLA alleles (including HLA-A*0207, HLA-A*2402, HLA-B*1301, HLA-B*1502, HLA-B*4001, HLA-B*4609, HLA-B*5101, HLA-DRB1*1001 or HLA-DRB1*1502) and phenytoin concentration in the patient's plasma can all contribute to phenytoin-induced ADRs.

Abstract: Disclosed herein are an oil-extracted product of indigo naturalis, and the preparation process thereof. Also disclosed are a pharmaceutical composition containing the oil-extracted product of indigo naturalis and a method for treating a human subject having or suspected to have a psoriatic disease such as skin psoriasis and nail psoriasis.