E2 Corporation: Since 1994
E2 American Artificial Intelligence Advancement Center
E2 Corporation: Since 1994
E2 American Artificial Intelligence Advancement Center
E2 Corporation is building JaviX as a solution provider related to World Class Diagnostics. Our mission is to make every basic Diagnostic necessary facility very affordable and reachable to a common man at their doorstep. We have started our journey in Healthcare industry space where we have credible knowledge backed with a lot of research information which complements what we do.
JaviX is a health innovation company specializing in clinical examination platforms. JaviX provides remote diagnostics, patient monitoring, cloud EMR analysis, telemedicine connectivity, and on-demand scheduling through interoperable examination platforms serviced by an array of connected devices.
“The future of healthcare is outside the walls of traditional facilities. PortaClinic™ is designed to keep patients out of tahe hospital and other high-cost care settings without sacrificing access to high-value clinical data.”
The global AI in healthcare market size is expected to grow from USD 4.9 billion in 2020 and reach USD 45.2 billion by 2026; it is projected to grow at a CAGR of 44.9% during the forecast period.
The major factors driving the market growth are:
- Increasing volume of healthcare data
- Growing complexities of datasets driving the need for AI
- The intensifying needs to reduce towering healthcare costs,
- Improving computing power and declining hardware costs
- Growing number of cross-industry partnerships and collaborations
- Rising imbalance between health workforce and patients driving the need for improvised healthcare services
E2 Corporation is focusing on Healthtech AI to deliver results on the technologies mentioned below
Machine learning is being adopted in healthcare to deal with large volumes of data, where the time previously dedicated for poring over charts and spreadsheets is now being used to seek intelligent ways to automate data analysis. It is used to streamline administrative processes in hospitals, map and treat infectious diseases, and personalize medical treatments. Machine learning includes various technologies, such as deep learning, supervised learning, unsupervised learning, and reinforcement learning. Imaging and diagnostics, and drug discovery are among the applications that use deep learning.
Machine learning is being adopted in healthcare to deal with large volumes of data, where the time previously dedicated for poring over charts and spreadsheets is now being used to seek intelligent ways to automate data analysis. It is used to streamline administrative processes in hospitals, map and treat infectious diseases, and personalize medical treatments. Machine learning includes various technologies, such as deep learning, supervised learning, unsupervised learning, and reinforcement learning. Imaging and diagnostics, and drug discovery are among the applications that use deep learning.
In healthcare, computer vision has shown significant application in surgery and therapy of a few diseases. Robotic surgery application uses computer vision to identify distances or specific body part. Computer vision systems offer precise diagnoses, thus minimizing false positives. The technology can potentially wipe out the requirement for redundant surgical procedures and expensive therapies. Computer vision algorithms that are trained using a huge amount of training data can detect the slightest presence of a condition which human doctors may miss because of their sensory limitations.
NLP is widely used by the clinical and research community in healthcare to develop and manage semi-structured and unstructured textual documents, such as electronics health reports, pathology reports, and clinical notes. The algorithm extracts the health problems from narrative text clinical documents and proposes for inclusion in a patient’s electronic problem list to interpret accurately. The demand for NLP has grown, with healthcare institutions using it to structure their clinical data and interpret more accurately. Moreover, the growing use of the Internet and connected devices, along with the huge volume of patients’ data, drives the growth of this market.
NLP is widely used by the clinical and research community in healthcare to develop and manage semi-structured and unstructured textual documents, such as electronics health reports, pathology reports, and clinical notes. The algorithm extracts the health problems from narrative text clinical documents and proposes for inclusion in a patient’s electronic problem list to interpret accurately. The demand for NLP has grown, with healthcare institutions using it to structure their clinical data and interpret more accurately. Moreover, the growing use of the Internet and connected devices, along with the huge volume of patients’ data, drives the growth of this market.