Abstract: A system is provided for use with an insulated boom section of a bucket truck. The system includes a source of high volume and pressure, dry air; one or more interior air diffusers connected to the source of high volume and pressure, dry air to direct the air into an interior of the insulated boom section. One or more exterior air diffusers connected to the source of high volume and pressure, dry air direct the air to along an exterior surface of the insulated boom section. A method is also provided for cleaning or drying both the interior and exterior surfaces simultaneously of an insulated boom section of the boom of a bucket truck. The boom of a bucket truck is further provided in another aspect that includes at least one insulated boom section, a source of high volume and pressure, dry air, one or more interior air diffusers and one or more exterior air diffusers. A pre-heating air heater may be removably mounted into the boom.

Abstract: Apparatuses, systems, methods, and computer program products are disclosed for medical assessment based on voice. A query module is configured to audibly question a user from an electronic display screen and/or a speaker of a computing device with one or more open ended questions. A response module is configured to receive a conversational verbal response of a user from a microphone of a computing device in response to one or more open ended questions. A detection module is configured to provide a machine learning assessment for a user of a medical condition based on a machine learning analysis of a received conversational verbal response of the user.

Abstract: A mathematical model may be trained to diagnose a medical condition of a person by processing acoustic features and language features of speech of the person. The performance of the mathematical model may be improved by appropriately selecting the features to be used with the mathematical model. Features may be selected by computing a feature selection score for each acoustic feature and each language feature, and then selecting features using the scores, such as by selecting features with the highest scores. In some implementations, stability determinations may be computed for each feature and features may be selected using both the feature selection scores and the stability determinations. A mathematical model may then be trained using the selected features and deployed. In some implementations, prompts may be selected using computed prompt selection scores, and the deployed mathematical model may be used with the selected prompts.

Abstract: Apparatuses, systems, methods, and computer program products are disclosed for medical assessment based on voice. A query module is configured to audibly question a user from an electronic display screen and/or a speaker of a computing device with one or more open ended questions. A response module is configured to receive a conversational verbal response of a user from a microphone of a computing device in response to one or more open ended questions. A detection module is configured to provide a machine learning assessment for a user of a medical condition based on a machine learning analysis of a received conversational verbal response of the user.

Abstract: Apparatuses, systems, methods, and computer program products are disclosed for medical assessment based on voice. A query module is configured to audibly question a user from a speaker of a mobile computing device with one or more open ended questions. A response module is configured to receive a conversational verbal response of a user from a microphone of a mobile computing device in response to one or more open ended questions. A detection module is configured to provide a machine learning assessment for a user of a medical condition based on a machine learning analysis of a received conversational verbal response of the user.

Abstract: A mathematical model may be trained to diagnose a medical condition of a person by processing acoustic features and language features of speech of the person. The performance of the mathematical model may be improved by appropriately selecting the features to be used with the mathematical model. Features may be selected by computing a feature selection score for each acoustic feature and each language feature, and then selecting features using the scores, such as by selecting features with the highest scores. In some implementations, stability determinations may be computed for each feature and features may be selected using both the feature selection scores and the stability determinations. A mathematical model may then be trained using the selected features and deployed. In some implementations, prompts may be selected using computed prompt selection scores, and the deployed mathematical model may be used with the selected prompts.

Abstract: A mathematical model may be trained to diagnose a medical condition of a person by processing acoustic features and language features of speech of the person. The performance of the mathematical model may be improved by appropriately selecting the features to be used with the mathematical model. Features may be selected by computing a feature selection score for each acoustic feature and each language feature, and then selecting features using the scores, such as by selecting features with the highest scores. In some implementations, stability determinations may be computed for each feature and features may be selected using both the feature selection scores and the stability determinations. A mathematical model may then be trained using the selected features and deployed. In some implementations, prompts may be selected using computed prompt selection scores, and the deployed mathematical model may be used with the selected prompts.

Abstract: Apparatuses, systems, methods, and computer program products are disclosed for medical assessment based on voice. A query module is configured to audibly question a user from a speaker of a mobile computing device with one or more open ended questions. A response module is configured to receive a conversational verbal response of a user from a microphone of a mobile computing device in response to one or more open ended questions. A detection module is configured to provide a machine learning assessment for a user of a medical condition based on a machine learning analysis of a received conversational verbal response of the user.

Abstract: Apparatuses, systems, methods, and computer program products are disclosed for medical assessment based on voice. A query module is configured to audibly question a user from a speaker of a mobile computing device. A response module is configured to receive a verbal response of a user from a microphone of a mobile computing device. A detection module is configured to provide an assessment for a user of a medical condition based on an analysis of a received verbal response of the user.

Abstract: A mathematical model may be trained to diagnose a medical condition of a person by processing acoustic features and language features of speech of the person. The performance of the mathematical model may be improved by appropriately selecting the features to be used with the mathematical model. Features may be selected by computing a feature selection score for each acoustic feature and each language feature, and then selecting features using the scores, such as by selecting features with the highest scores. In some implementations, stability determinations may be computed for each feature and features may be selected using both the feature selection scores and the stability determinations. A mathematical model may then be trained using the selected features and deployed. In some implementations, prompts may be selected using computed prompt selection scores, and the deployed mathematical model may be used with the selected prompts.

Abstract: A mathematical model may be trained to diagnose a medical condition of a person by processing acoustic features and language features of speech of the person. The performance of the mathematical model may be improved by appropriately selecting the features to be used with the mathematical model. Features may be selected by computing a feature selection score for each acoustic feature and each language feature, and then selecting features using the scores, such as by selecting features with the highest scores. In some implementations, stability determinations may be computed for each feature and features may be selected using both the feature selection scores and the stability determinations. A mathematical model may then be trained using the selected features and deployed. In some implementations, prompts may be selected using computed prompt selection scores, and the deployed mathematical model may be used with the selected prompts.

Abstract: A mathematical model may be trained to diagnose a medical condition of a person by processing acoustic features and language features of speech of the person. The performance of the mathematical model may be improved by appropriately selecting the features to be used with the mathematical model. Features may be selected by computing a feature selection score for each acoustic feature and each language feature, and then selecting features using the scores, such as by selecting features with the highest scores. In some implementations, stability determinations may be computed for each feature and features may be selected using both the feature selection scores and the stability determinations. A mathematical model may then be trained using the selected features and deployed. In some implementations, prompts may be selected using computed prompt selection scores, and the deployed mathematical model may be used with the selected prompts.

Abstract: Apparatuses, systems, methods, and computer program products are disclosed for medical assessment based on voice. A query module is configured to audibly question a user from a speaker of a mobile computing device. A response module is configured to receive a verbal response of a user from a microphone of a mobile computing device. A detection module is configured to provide an assessment for a user of a medical condition based on an analysis of a received verbal response of the user.