Abstract: Embodiments relate to digital image processing for diagnosis of a subject. More specifically, the embodiments relate to automation of diagnoses through data interpretation. An image is acquired from the subject. Elements are recognized within the image based on morphological features. The image is compared to learned data. Based on the comparison, a probability of a potential diagnosis(es) is calculated. A diagnosis of the subject is determined based on the potential diagnosis(es) and the calculated probability. The diagnosis may be changed based on a new image acquired from the subject.

Abstract: A method, system, and computer program product for determining and improving treatment points includes: receiving an identification of a problem area provided by a user; receiving instructions for treating the problem area from a server, the instructions including at least suggested treatment points; generating an output of the suggested treatment points, where the output transmits the suggested treatment points to the user; monitoring real time treatment responses of the user, the treatment responses including at least one of biometric responses and treatment gestures at the problem area; analyzing the treatment responses; generating adjusted treatment points based on the analyzing; generating treatment records based on the treatment responses and the adjusted treatment points, where the treatment records indicates a result of the suggested treatment points; and transmitting the treatment records to the server to enable the server to generate a treatment template of the user.

Abstract: A method, system, and computer program product for determining and improving treatment points includes: configuring one or more treatment templates, the one or more treatment templates including service criteria and treatment points; receiving a treatment request from a computing device, the treatment request including an identification of a problem area of a user of the computing device; selecting a first treatment template from the one or more treatment templates based on the treatment request, the first treatment template including treatment points; transmitting the treatment points from the treatment template to the computing device; collecting patient treatment responses from the computing device; analyzing the treatment responses using natural language processing, image analysis, and learning modules; identifying adjusted treatment points based on the analysis; generating a second treatment template using the patient treatment responses and the adjusted treatment points.

Abstract: Utilizing a computing device executing a master chatbot and one or more modular chatbots to respond to one or more chat messages. A computing device executing the master chatbot receives one or more chat messages. The computing device parses the received one or more chat messages to discover an intent and entities contained within the chat messages. A ranking algorithm is employed to rank the master chatbot and a plurality of modular chatbots, the ranking algorithm scoring the master chatbot and the plurality of modular chatbots based upon the intent and entities contained within the one or more chat messages. The master chatbot responds to the chat message if the ranking algorithm rates the master chatbot highest or forwards automatically the one or more chat messages to a ranked modular chatbot for response if the ranking algorithm rates the ranked modular chatbot highest.

Abstract: Embodiments relate to digital image processing for diagnosis of a subject. More specifically, the embodiments relate to automation of diagnoses through data interpretation. An image is acquired from the subject. Elements are recognized within the image based on morphological features. The image is compared to learned data. Based on the comparison, a probability of a potential diagnosis(es) is calculated. A diagnosis of the subject is determined based on the potential diagnosis(es) and the calculated probability. The diagnosis may be changed based on a new image acquired from the subject.

Abstract: In an approach to enhancing the security features of user interfaces of computing devices, a computing device repeatedly detects environmental cues in its vicinity. The computing device determines the presence of a threat based on matching at least one of the detected environmental cues with one or more stored threat criteria. The computing device determines the presence of one or more sensitive applications on a user interface. Having determined the presence of one or more sensitive applications on the user interface, the computing device hides the one or more sensitive applications.

Abstract: A security aware email server and a method of managing incoming email are described. The server includes a memory device configured to store rules, instructions, and user preferences. The processor makes a determination of whether a sender of an incoming email used a secure or unsecure sending network to send the email and determines an action to take with the email based on the determination and the user preferences.

Abstract: Embodiments relate to digital image processing for diagnosis of a subject. More specifically, the embodiments relate to automation of diagnoses through data interpretation. An image is acquired from the subject. Elements are recognized within the image based on morphological features. The image is compared to learned data. Based on the comparison, a probability of a potential diagnosis(es) is calculated. A diagnosis of the subject is determined based on the potential diagnosis(es) and the calculated probability. The diagnosis may be changed based on a new image acquired from the subject.

Abstract: Embodiments relate to digital image processing for diagnosis of a subject. More specifically, the embodiments relate to automation of diagnoses through data interpretation. An image is acquired from the subject. Elements are recognized within the image based on morphological features. The image is compared to learned data. Based on the comparison, a probability of a potential diagnosis(es) is calculated. A diagnosis of the subject is determined based on the potential diagnosis(es) and the calculated probability. The diagnosis may be changed based on a new image acquired from the subject.

Abstract: Embodiments relate to digital image processing for diagnosis of a subject. More specifically, the embodiments relate to automation of diagnoses through data interpretation. An image is acquired from the subject. Elements are recognized within the image based on morphological features. The image is compared to learned data. Based on the comparison, a probability of a potential diagnosis(es) is calculated. A diagnosis of the subject is determined based on the potential diagnosis(es) and the calculated probability. The diagnosis may be changed based on a new image acquired from the subject.

Abstract: Embodiments relate to digital image processing for diagnosis of a subject. More specifically, the embodiments relate to automation of diagnoses through data interpretation. An image is acquired from the subject. Elements are recognized within the image based on morphological features. The image is compared to learned data. Based on the comparison, a probability of a potential diagnosis(es) is calculated. A diagnosis of the subject is determined based on the potential diagnosis(es) and the calculated probability. The diagnosis may be changed based on a new image acquired from the subject.

Abstract: Embodiments relate to digital image processing for diagnosis of a subject. More specifically, the embodiments relate to automation of diagnoses through data interpretation. An image is acquired from the subject. Elements are recognized within the image based on morphological features. The image is compared to learned data. Based on the comparison, a probability of a potential diagnosis(es) is calculated. A diagnosis of the subject is determined based on the potential diagnosis(es) and the calculated probability. The diagnosis may be changed based on a new image acquired from the subject.

Abstract: Embodiments relate to digital image processing for diagnosis of a subject. More specifically, the embodiments relate to automation of diagnoses through data interpretation. An image is acquired from the subject. Elements are recognized within the image based on morphological features. The image is compared to learned data. Based on the comparison, a probability of a potential diagnosis(es) is calculated. A diagnosis of the subject is determined based on the potential diagnosis(es) and the calculated probability. The diagnosis may be changed based on a new image acquired from the subject.

Abstract: Described herein is a system and method for addition of content to a question answer (QA) system. The method may comprise retrieving, from a template store of the QA system, a template comprising one or more data fields and one or more metadata fields. The method may further comprise populating a passage field with passage information, wherein the passage field is one of the one or more data fields. The method may further comprise populating a training field with training information, wherein the training field is one of the one or more metadata fields. The method may further comprise ingesting, into a corpus of the QA system, a completed template comprising a populated passage field and a populated training field into the corpus.

Abstract: A system and a computer program product are provided for evaluating question-answer pairs in an answer key by comparing a first answer key answer to a plurality of candidate answers to determine if the answer key may have a problem if the plurality of candidate answers are more similar to one another than to the first answer and to determine if the plurality of candidate answers has gradient information which may be used to update the answer key if not already included in the answer key.

Abstract: A security aware email server and a method of managing incoming email are described. The server includes a memory device configured to store rules, instructions, and user preferences. The processor makes a determination of whether a sender of an incoming email used a secure or unsecure sending network to send the email and determines an action to take with the email based on the determination and the user preferences.

Abstract: In an approach to enhancing the security features of user interfaces of computing devices, a computing device repeatedly detects environmental cues in its vicinity. The computing device determines the presence of a threat based on matching at least one of the detected environmental cues with one or more stored threat criteria. The computing device determines the presence of one or more sensitive applications on a user interface. Having determined the presence of one or more sensitive applications on the user interface, the computing device hides the one or more sensitive applications.

Abstract: A security aware email server and a method of managing incoming email are described. The server includes a memory device configured to store rules, instructions, and user preferences. The processor makes a determination of whether a sender of an incoming email used a secure or unsecure sending network to send the email and determines an action to take with the email based on the determination and the user preferences.

Abstract: A security aware email server and a method of managing incoming email are described. The server includes a memory device configured to store rules, instructions, and user preferences. The processor makes a determination of whether a sender of an incoming email used a secure or unsecure sending network to send the email and determines an action to take with the email based on the determination and the user preferences.

Abstract: A security aware email server and a method of managing incoming email are described. The server includes a memory device configured to store rules, instructions, and user preferences. The processor makes a determination of whether a sender of an incoming email used a secure or unsecure sending network to send the email and determines an action to take with the email based on the determination and the user preferences.