Abstract: Discussed herein are an apparatus and a corresponding method for classifying a murmur detected in a heart signal as a Still's murmur. Circuitry included in the apparatus segments a heart signal to detect a first lobe (S1) and a second lobe (S2) of the heart signal. Further, the circuitry computes a spectral width of an extracted feature of the heart signal that lies in a portion of a time interval between the S1 lobe and the S2 lobe based on an estimated power spectral density. Additionally, a peak frequency of the extracted feature of the heart signal and a shape of an envelope of the extracted feature of the heart signal are computed. The extracted feature of the heart signal is classified as the Still's murmur based on the spectral width, the peak frequency, the shape of the envelop, and additional murmur discriminant features.

Abstract: A claims preprocessor processes claim data to identify claims that are to be adjudicated. Each claim includes at least one claim exception. The claims preprocessor further prioritizes the claim exception of each identified claim based on the claim data. A robotic process automator then orchestrates adjudication of the identified claims based on claim data. Further, a rules engine adjudicates the identified claims based on pre-defined rules. Subsequently, a fall out handler determines if any of the identified claims are incorrectly adjudicated and identify an issue associated with incorrect claims adjudication on determining that any of the identified claims are incorrectly adjudicated. A self learner then provides feedback to rules engine based on a decision tree and information received from fall out handler, the feedback being usable to resolve the issue. The information received from fall out handler is indicative of issue associated with incorrect claims adjudication.

Abstract: Discussed herein are an apparatus and a corresponding method for classifying a murmur detected in a heart signal as a Still's murmur. Circuitry included in the apparatus segments a heart signal to detect a first lobe (S1) and a second lobe (S2) of the heart signal. Further, the circuitry computes a spectral width of an extracted feature of the heart signal that lies in a portion of a time interval between the S1 lobe and the S2 lobe based on an estimated power spectral density. Additionally, a peak frequency of the extracted feature of the heart signal and a shape of an envelope of the extracted feature of the heart signal are computed. The extracted feature of the heart signal is classified as the Still's murmur based on the spectral width, the peak frequency, the shape of the envelop, and additional murmur discriminant features.