Abstract: An electronic device has a narrow viewing angle state and a wide viewing angle state, and includes a panel and a light source providing a light passing through the panel. In the narrow viewing angle state, the light has a first relative light intensity and a second relative light intensity. The first relative light intensity is the strongest light intensity, the second relative light intensity is 50% of the strongest light intensity, the first relative light intensity corresponds to an angle of 0°, the second relative light intensity corresponds to a half-value angle, and the half-value angle is between ?15° and 15°. In the narrow angle state, a third relative light intensity at each angle between 20° and 60° or each angle between ?20° and ?60° is lower than 20% of the strongest light intensity.

Abstract: A system for assessing extubation includes a respiratory assistance device, an artificial intelligence platform, and a hospital information system. The respiratory assistance device is adapted to communicate with a trachea of a patient. The artificial intelligence platform includes a prediction module. A method for assessing extubation includes the following steps. Measured values of respiratory parameters of the patient are recorded by the respiratory assistance device. The recorded times and the measured values of the respiratory parameters corresponding to each of the recording times are transmitted to the artificial intelligence platform. The prediction module analyzes the measured values of respiratory parameters within a predetermined time period according to a prediction model to generate a prediction result. The prediction result is transmitted to the hospital information system and is recorded into a medical record of the patient.

Abstract: A system for assessing extubation includes a respiratory assistance device, an artificial intelligence platform, and a hospital information system. The respiratory assistance device is adapted to communicate with a trachea of a patient. The artificial intelligence platform includes a prediction module. A method for assessing extubation includes the following steps. Measured values of respiratory parameters of the patient are recorded by the respiratory assistance device. The recorded times and the measured values of the respiratory parameters corresponding to each of the recording times are transmitted to the artificial intelligence platform. The prediction module analyzes the measured values of respiratory parameters within a predetermined time period according to a prediction model to generate a prediction result. The prediction result is transmitted to the hospital information system and is recorded into a medical record of the patient.