Abstract: A method and an apparatus related to medication list management are provided. The medication association between one or more diagnoses and one or more corresponding medications recorded in a medical record is determined through an evaluating model. The evaluating model is trained through a machine learning algorithm. Multiple medication categories are integrated into the medical record based on the medication association. The medication includes one or both of a first medication and a second medication. The medication categories include an explained category related to the first medication with higher medication association and an unexplained category related to the second medication with lower medication association. A medication list interface presenting the medical record with multiple medication categories is provided. Accordingly, the medication history would be structured, grouped, and visual-encoded, so as to provide an intuitive medication list.

Abstract: The disclosure provides a method for providing visualized clinical information and an electronic device.

Abstract: A multi-input multi-output adder and an operating method thereof are proposed. The multi-input multi-output adder includes an adder circuitry configured to perform an operation. The operation includes the following. A first source operand and a second source operand are added to generate a first summed operand. Direct truncation is performed on at least one last bit of the first summed operand to generate a first truncated-summed operand. Right shift is performed on the first truncated-summed operand to generate a first shifted-summed operand. A bit number of the right shift of the first truncated-summed operand is equal to a bit number of the direct truncation of the first summed operand.

Abstract: A clinical association evaluating apparatus and a clinical association evaluating method are provided. In the method, association coefficients between multiple diseases and medicines are determined through an evaluating model. The evaluating model is trained through a machine learning algorithm. The first association between each medicine and the disease with the highest association coefficient is maintained, and the second association between each medicine and the disease without the highest association coefficient is disconnected. The association coefficients between the medicines and the diseases are modified according to the maintained first association and the disconnected second association. Accordingly, the modified association coefficients are adapted for clinical application, and false associations could be removed.

Abstract: The present disclosure provides computed-implemented method and computing device for predicting cancer. The computing device: retrieves an electronic medical record of a user from a database; transform the electronic medical record into a matrix; and determine a cancer prediction result corresponding to the matrix according to a cancer prediction model.

Abstract: An apparatus and a method for processing a prescription are introduced. The apparatus includes at least one non-transitory computer-readable medium and at least one processor. The at least one non-transitory computer-readable medium and computer executable instructions are configured to, with the at least one processor, cause the apparatus to perform: receiving a first code set comprising at least one diagnosis code and at least one medicine code classification codes; outputting one or more medicine codes of the first code set; receiving a first signal responsive to the output medicine codes; and updating first weights and second weights associated with the output medicine codes in a database in communication with the at least one processor. Therefore, the apparatus and method enhance the accuracy of prescriptions, reduce likelihood of medication errors, cut medical expenditure, and save patients' lives.

Abstract: The present disclosure provides computing device, portable device and computed-implemented method for predicting and monitoring Major Adverse Cardiovascular Events (MACE). A MACE prediction model is generated according to a machine learning scheme with training data of a plurality of user data. A MACE occurrence level is determined according to selected variables associated with MACE.

Abstract: A method and a system for identifying skin texture and skin lesion using artificial intelligence cloud-based platform are provided. The system includes an electronic device and a server. The server includes a storage device and a processor. The processor is coupled to the storage device, and accesses and executes multiple modules stored in the storage device. The multiple modules include an information receiving module, for receiving a captured image and multiple user parameters; a feature vector obtaining module, for obtaining a first feature vector of the captured image and calculating a second feature vector of the multiple user parameters; a skin parameter obtaining module, for obtaining an output result associated with skin parameters according to the first feature vector and the second feature vector; and a skin identification module, for determining a skin identification result according to the output result of the skin parameters.

Abstract: The present application discloses a method for adjusting environment via a mobile app, comprising: selecting a control mode, wherein the control mode comprises a voice mode and a touch mode; selecting a control option, wherein the control option comprises a bed control option, a light control option, an equipment control option and a calling option; and adjusting a bed, a light or an equipment or calling for help, wherein the equipment comprises a curtain, a television, music or an air conditioner. The present application also discloses a mobile app comprising three control interfaces. The first control interface comprises a voice mode button and a touch mode button. The second control interface comprises a bed control button, a light control button, an equipment control button and a calling button. The third control interface enables a user to adjust a bed, lights, equipment or call for help.

Abstract: A prescription analysis system and method are introduced. The prescription analysis system includes a knowledge database, an access module, a storage module, and a judgment module. The judgment module judges whether a new prescription is appropriate according to three prescription appropriateness criteria. The prescription analysis method is integrated in the prescription analysis system. Therefore, the prescription analysis system and method enhance the accuracy of prescriptions, reduce likelihood of medication errors, cut medical expenditure, and save patients' lives.