Abstract: The disclosed embodiments relate to system, method and apparatus for forming ML sessions so that an AI system can identify, track and diagnose a user through the user's bathroom sessions. As used herein, a session is a period of time during which a user is active in the toilet. The session may include certain inactivity if such inactivity lasts only for a predefined duration. In an exemplary embodiment, a system is configured to capture images of excreta and, using ML algorithms, classifies the toileting session using Digital Biomarkers (DBMs). The ability to create an excreta log to accurately deliver detailed information to doctors and healthcare providers can revolutionize healthcare by notifying when further urine or fecal screening is necessary. The disclosed embodiments of ML and image identification through AI requires no user behavior change and provides a link between medical records and specific excreta patterns.

Abstract: The disclosed embodiments relate to system, method and apparatus for forming ML sessions so that an AI system can identify, track and diagnose a user through the user's bathroom sessions. As used herein, a session is a period of time during which a user is active in the toilet. The session may include certain inactivity if such inactivity lasts only for a predefined duration. In an exemplary embodiment, a system is configured to capture images of excreta and, using ML algorithms, classifies the toileting session using Digital Biomarkers (DBMs). The ability to create an excreta log to accurately deliver detailed information to doctors and healthcare providers can revolutionize healthcare by notifying when further urine or fecal screening is necessary. The disclosed embodiments of ML and image identification through AI requires no user behavior change and provides a link between medical records and specific excreta patterns.

Abstract: The disclosed embodiments relate to system, method and apparatus for forming ML sessions so that an AI system can identify, track and diagnose a user through the user's bathroom sessions. As used herein, a session is a period of time during which a user is active in the toilet. The session may include certain inactivity if such inactivity lasts only for a predefined duration. In an exemplary embodiment, a system is configured to capture images of excreta and, using ML algorithms, classifies the toileting session using Digital Biomarkers (DBMs). The ability to create an excreta log to accurately deliver detailed information to doctors and healthcare providers can revolutionize healthcare by notifying when further urine or fecal screening is necessary. The disclosed embodiments of ML and image identification through AI requires no user behavior change and provides a link between medical records and specific excreta patterns.

Abstract: The disclosed embodiments relate to system, method and apparatus for forming ML sessions so that an AI system can identify, track and diagnose a user through the user's bathroom sessions. As used herein, a session is a period of time during which a user is active in the toilet. The session may include certain inactivity if such inactivity lasts only for a predefined duration. In an exemplary embodiment, a system is configured to capture images of excreta and, using ML algorithms, classifies the toileting session using Digital Biomarkers (DBMs). The ability to create an excreta log to accurately deliver detailed information to doctors and healthcare providers can revolutionize healthcare by notifying when further urine or fecal screening is necessary. The disclosed embodiments of ML and image identification through AI requires no user behavior change and provides a link between medical records and specific excreta patterns.

Abstract: The disclosed embodiments relate to system, method and apparatus for forming ML sessions so that an AI system can identify, track and diagnose a user through the user's bathroom sessions. As used herein, a session is a period of time during which a user is active in the toilet. The session may include certain inactivity if such inactivity lasts only for a predefined duration. In an exemplary embodiment, a system is configured to capture images of excreta and, using ML algorithms, classifies the toileting session using Digital Biomarkers (DBMs). The ability to create an excreta log to accurately deliver detailed information to doctors and healthcare providers can revolutionize healthcare by notifying when further urine or fecal screening is necessary. The disclosed embodiments of ML and image identification through AI requires no user behavior change and provides a link between medical records and specific excreta patterns.

Abstract: Provided are computer systems, methods, and non-transitory computer-readable medium configured for analyzing and using screenshots. The analysis and use can entail receiving a screenshot comprising identifying information of a merchandise, retrieving a candidate merchandise, offered for sale by a vendor, which candidate merchandise is a potential match to the merchandise according to the identifying information; and displaying the candidate merchandise.

Abstract: Provided are computer systems, methods, and non-transitory computer-readable medium configured for analyzing and using screenshots. The analysis and use can entail receiving a screenshot comprising identifying information of a merchandise, retrieving a candidate merchandise, offered for sale by a vendor, which candidate merchandise is a potential match to the merchandise according to the identifying information; and displaying the candidate merchandise.