Simbo is one of the most progressive and natural upgrade in the medicinal field with its human-like skills to comprehend all healthcare stakeholders' needs. Simbo, with its human-like intelligence is skilled to assist doctors in their day to day tasks, ensuring they focus only on treating Patients.
Revolutionary AI based on proprietary BISLU (Brain Inspired Spoken Language Understanding) platform powered by GIPCA (General Intellience Predictive and Corrective Architecture).
Voice-based, secure and HIPAA compliant assistant for efficient clinical documentation.
A digital assistant acting like a real doctor helping in pre-screening and documentation
Today when the world is running behind AI, we are creating world's most shrewd technology using NeuroSymbolic AI to get human-like understanding of our world. BISLU with proprietary Thought Representation Ecosystem creates an intelligent low-power technology. In a nutshell, say what you want in a single line or in as many sentences as you want, BISLU will know what you are saying.
GIPCA (General Intelligence Predictive and Corrective Architecture) is a proprietary architecture and one of the basic building blocks for BISLU. As the names suggests, it is a basic unit which not only predicts output but also corrects it. It uses both supervised & unsupervised learning techniques and hence uses much smaller training datasets.
BISLU (Brain Inspired Spoken Language Understanding) is a single unified Spoken Language Understanding architecture which uses general intelligence algorithms beyond AI/ML to create a general-purpose language understanding model. BISLU uses ANN, Symbolic AI, Knowledge Bases, Predictive Memories, and many more brain-inspired algorithms to achieve this.
World's first Thought Representation Ecosystem, comprising of unique tools for representing complicated human-like connected thought structures on computers with ease. Proprietary language called ETML (Extended Thought Mark-up Langauge) is used to encode structured-data representing human thoughts.
Our Neuro-Symbolic AI Models are Designed to be Lean on Data
This dataset is made up of prescription-images and their data-content in structured format as Electronic Medical Records (EMR) duly verified by clinician. Structured data has a very detailed schema - eg. attributes for medications prescribed are: med-name, code, mode of administration, dosage or quantity, frequency, duration, whether before/after food. Majority of prescription-images are hand-written notes while a few have printed content. The top specialities are: GP, Pediatrics, Gynae, Neuro, Cardio, Ortho and Gastro. These records are from various departments such as Out-Patient, In-Patient (discharge-summaries), Emergency, Pathology/Radiology (investigation-reports).
see moreFor Acoustic Model:
The STT dataset is a combination of our proprietary medical recordings dataset taken from Health-PIE and newly generated sentences. The medical recordings dataset comprises millions of text and their corresponding Indian-accent recordings in the English language. This dataset is one of its kind as it has a wide variety in medical terminology as well as in general English sentences (common descriptive sentences and phrases).
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