Abstract: The spin column of the present invention is used for filtering and extracting biological molecules, such as nucleic acids and proteins. When the spin column is used, it is placed inside a collection tube, which is then placed in a centrifuge slot and the centrifuge is activated. The internal volume of the spin column of the present invention is larger than that of a conventional spin column, allowing it to accommodate a larger amount of specimens. Additionally, the filter membrane positioned inside the spin column of the present invention is smaller than that of conventional spin columns. The amount of washing solution required to wash the biological molecules from the filter membrane is proportional to the size of the filter membrane. Therefore, less washing solution is required in the present invention. Since the spin column of the present invention can accommodate a larger amount of specimen, the number of biomolecules contained in the specimen is also larger.

Abstract: A training data processing method and an electronic device are provided. The method includes: obtaining medical history data including at least one first disease suffered by a user; setting a plurality of disease types according to a target disease; setting a time interval; obtaining at least one second disease in the time interval from the medical history data; performing a pre-processing operation on the second disease according to the disease types to obtain processed data; and inputting the processed data to a neural network to train the neural network.

Abstract: A training data processing method and an electronic device are provided. The method includes: obtaining medical history data including at least one first disease suffered by a user; setting a plurality of disease types according to a target disease; setting a time interval; obtaining at least one second disease in the time interval from the medical history data; performing a pre-processing operation on the second disease according to the disease types to obtain processed data; and inputting the processed data to a neural network to train the neural network.

Abstract: A method and an electronic device of checking drug interaction are provided. The method includes: generating a first odds ratio (OR) between a first drug combination and a hospitalization event, a second OR between a second drug combination and the hospitalization event, and a third OR between a third drug combination and the hospitalization event according to a plurality of medical records; generating a first fraction corresponding to a first drug according to the second OR; generating a second fraction corresponding to a second drug according to the third OR; and outputting the first drug combination in response to the first OR being greater than a first threshold, a sum of the first fraction and the second fraction being greater than a second threshold, and a quotient of the first fraction and the second fraction being less than a third threshold.

Abstract: A medication risk evaluation method and a medication risk evaluation device are provided. The medication risk evaluation method includes: obtaining first medication route information related to a first medicine combination in a medication database; obtaining second medication route information related to a second medicine combination in the medication database; obtaining overlapping medication information between the first medication route information and the second medication route information; determining whether the overlapping medication information meets a noise exclusion condition; and if the overlapping medication information meets the noise exclusion condition, establishing a risk evaluation model based on other medication route information in the medication database excluding the first medication route information, where the risk evaluation model is adapted to evaluate a risk of using at least one medicine in the medication database.

Abstract: A method for calculating a high risk route of administration is provided. Multiple arrangement routes composed of every two medicines among multiple medicines included in a medical record database are listed. A risk value of each arrangement route is calculated by querying the medical record database based on a specified medication result. A risk score of each arrangement route is calculated according to the risk value, and the arrangement routes are sorted based on the risk scores. Starting from the arrangement route with the highest risk score, N arrangement routes are retrieved and a combination on N of the arrangement routes is performed to obtain multiple strung routes. The number of medicines included in each strung route matches a specified medication number.

Abstract: The present invention reveals a tool changing method for machine tool and the apparatus thereof. The machine tool has a tool releasement detector disposed beside the spindle or the tool releasement apparatus. When the tool releasement apparatus hits the spindle to loose the clamp for tool releasement, the tool releasement detector generates a releasement signal. When the tool releasement apparatus resets and leaves the spindle, the tool releasement detector produces no signal. The tool changing apparatus is activated according the appearance of the releasement signal for changing the tool, activated according the disappearing of the releasement signal for declining from the spindle. Therefore, the tool changing apparatus can be operated timely and speedily, improving tool changing efficiency.

Abstract: A training data processing method and an electronic device are provided. The method includes: obtaining medical history data including at least one first disease suffered by a user; setting a plurality of disease types according to a target disease; setting a time interval; obtaining at least one second disease in the time interval from the medical history data; performing a pre-processing operation on the second disease according to the disease types to obtain processed data; and inputting the processed data to a neural network to train the neural network.

Abstract: A method for organizing an electric energy and a kinetic energy of an electric vehicle includes the following steps. A plurality of electro-motor modules having different grade of kinetic energy are provided. A plurality of battery modules having different grade of electric energy are provided. A plurality of electric vehicle performances are preset, and one of the battery modules on the electric vehicle is arranged in accordance with the electric vehicle performances. One of the electro-motor modules on the electric vehicle is arranged in accordance with the electric vehicle performances and the one of the battery modules.

Abstract: A method for organizing an electric energy and a kinetic energy of an electric vehicle includes the following steps. A plurality of electro-motor modules having different grade of kinetic energy are provided. A plurality of battery modules having different grade of electric energy are provided. A plurality of electric vehicle performances are preset, and one of the battery modules on the electric vehicle is arranged in accordance with the electric vehicle performances. One of the electro-motor modules on the electric vehicle is arranged in accordance with the electric vehicle performances and the one of the battery modules.

Abstract: A decoder and partaker union device has a decoder, a first partaker, and a coaxial cable connected to the decoder and the first partaker. The decoder has a first radio frequency output terminal, a first frequency mixer, a first breaker, a second radio frequency output terminal, a first remote-control receiving detector, and an integrated circuit control board. The first partaker has a second radio frequency output terminal, a second breaker, a second frequency mixer, a first radio frequency input terminal, a third remote-control receiving detector, and a first power supply device.