Anumana, Inc.

Yogisha Heggadahalli Jayendra

Animesh Agarwal

Karthik K Bharadwaj

Rakesh Barve

Rohit Jain

Deepak Anand

Sughosh Indurkar

Shashi Kant

Anand Ramani

Shiva Verma

Sanjeev Shrinivas Nadapurohit

An apparatus and method for generating clinical decision support is disclosed. The apparatus includes at least a processor and a computer-readable storage medium communicatively connected to the at least a processor, wherein the computer-readable storage medium contains instructions configuring the at least processor to receive user data, generate a fused feature vector correlating the user data to a plurality of clinical outcomes by training a plurality of deep neural networks (DNNs) to output a first set of feature vectors, a second set of feature vectors and a third set of feature vectors, fusing the first, second, and third set of features vectors to form the fused feature vector, generate a procedural output using the fused feature vector, and display the procedural output through a user interface.

Apparatus and method for generating clinical decision support

A system for determining position signals of electrodes using a retrained machine-learning model includes at least a catheter including a plurality of electrodes configured to collect a plurality of potential signals and a magnetic sensor configured to collect magnetic data, and at least a computing device including a memory. The processor receives a first training set, wherein the first training set includes patient-agnostic data; receives a second training set, wherein the second training set includes patient-specific data, trains a mapping machine-learning model using the first training set, retrains the mapping machine-learning model using the second training set, receives at least a first signal, wherein the first signal includes a potential signal of the plurality of potential signal and the magnetic data, and generates, using the retrained machine-learning model, as a function of the at least a first signal, a first position signal for an electrode of the plurality of electrodes.

Methods and systems for determining position signals of electrodes using a retrained machine-learning model

An apparatus for the generation of an impedance model of a biological chamber is disclosed. The apparatus includes a catheter assembly comprising a plurality of electrodes arranged into one or more constraint pairs. The apparatus includes a processor and a memory communicatively connected to the processor. The memory instructs the processor to receive tank data. The memory instructs the processor to generate a plurality of relative configurations of the plurality of electrodes as a function of the tank data using a compliant configuration generator. The memory instructs the processor to record voltage data from the plurality of electrodes within a biological chamber as a function of the plurality of relative configurations. The memory instructs the processor to map a plurality of impedance metrics for each relative configuration as a function of the voltage data. The memory instructs the processor to generate an impedance model as a function of the map.

Apparatus and a method for the generation of an impedance model of a biological chamber

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Bengaluru, India

Yogisha Heggadahalli Jayendra