X-pulse is here to revolutionize and upgrade the provision of medical management. X-Pulse is one of the best representative cases of Artificial Intelligence being used in the field of Health Care. It has come to the market as an assistive tool to create convenience and its future is limitless. X-pulse is software that can read and analyze an X-ray to generate a report. With this ability it can play an instrumental role in supporting and easing decision making, providing consultation for the doctors and radiologists, cutting the time lags on reporting, delivering quick diagnosis on issues especially pertaining to serious health conditions and minimizing the probability of errors regarding report analysis by acting as an aide to the expert using it.
An AI-powered X-Ray diagnosis tool
Radiology-level
on chest X-Rays using Artificial Intelligence Technology
We have developed algorithms that can detect abnormalities from chest X-Rays at a clinically significant level benefiting Radiologists and Doctors.
AI for Radiologists
Decision Support
Our algorithm can help doctors understand X-rays and reduce subjectivity in diagnosis. This increases the accuracy of the report helping Doctors diagnose illness.
Reduce Reporting Delays
Once fine-tuned, our algorithms work in seconds to reach a diagnosis. The subsequent Natural Language Processing generated report enables a fully documented diagnosis. This capability addresses the International shortage of Radiologists helping both patients and Doctors.
Reduce Interpretation Errors
It is common for different Doctors to have different opinions about X-Rays. Our algorithms support the Doctors with an impartial opinion for them to compare their thoughts against.
Backlogs
Due to the speed of our algorithms and automated report generation capability, the overall number of backlogs will be reduced. This is important for both patients and Doctors since critical illnesses will be detected earlier leading to an increased chance of survival.
Problem?
With approximately 2 billion procedures per year, chest X-Rays are the most common and the most effective image examination tool. X-Rays provide critical illness screening, diagnosis, and management of diseases including pneumonia. However, an estimated two-thirds of the global population lack access to X-Ray diagnostics.
AI Modules
Severity
In addition to detection and localisation of diseases, our algorithms can detect the present and future probable severity, allowing healthcare providers to preemptively intervene and ensure better health.
Detection
AI-aided interpretation with significantly improved detection of pulmonary diseases on chest x-rays as compared with unaided interpretation.
Image Segmentation
Image segmentation is commonly used for measuring and visualizing the chest's anatomical structures, analyzing changes, delineating pathological regions, and for surgical planning and image-guided interventions. Our algorithms help radiologists quickly identify regions of interest without relying on subjective analysis methods.
Report Generation
A comprehensive understanding of vision and language and their interrelation are crucial to realize the underlying similarities and differences between these modalities and to learn more generalized, meaningful representations. With interest placed on learning the similarities between the embedding spaces across modalities, our algorithm utilizes a novel supervised deep learning-based approach in tandem with sentence-level LSTM-based text-autoencoder towards learning the embedding spaces to generate clinical analysis reports from the X-Rays, substantially reducing radiological diagnosis pipeline.
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