At SciX, we are disrupters of health-related AI-powered, Machine Learning applications stacked on blockchain technology, used for aggregation of data collections and biosensors on devices that predict and monitor patient's medical conditions remotely using scientific research conducted through the NIH, Research 1 universities and various scientists in the areas of health and wellness, nutrition, neuroscience, pharmacology, and advanced medicine. The ecosystem will include the use of biosensors that are programmed within a permissioned blockchain modeling a hyperledger fabric model setup by top engineers that enable the prediction and distribution of new variants of collective health data and the collection of research data that increases medical response time, alertness, and awareness by health care professionals. Some of these applications and devices include:
- Existing medical applications and medically used IoT devices registered with the system
- Patient data and IDs masked within...
At SciX, we are disrupters of health-related AI-powered, Machine Learning applications stacked on blockchain technology, used for aggregation of data collections and biosensors on devices that predict and monitor patient's medical conditions remotely using scientific research conducted through the NIH, Research 1 universities and various scientists in the areas of health and wellness, nutrition, neuroscience, pharmacology, and advanced medicine. The ecosystem will include the use of biosensors that are programmed within a permissioned blockchain modeling a hyperledger fabric model setup by top engineers that enable the prediction and distribution of new variants of collective health data and the collection of research data that increases medical response time, alertness, and awareness by health care professionals. Some of these applications and devices include:
- Existing medical applications and medically used IoT devices registered with the system
- Patient data and IDs masked within a permissioned-based platform
- Decentralized applications interconnected by medical devices that track and log vitals;
- Applications that run Proof of Change algorithms to detect and predict changes in an individual's body further based on a consensus algorithm that tracks and changes baseline treatment and thresholds with the system by comparative analytics triggered by his/her medical health condition tracking and patient log information to determine new variants and improve the health concerns of networks of users.

Examples of these biosensing differences include, but are not limited to, changes in oxygen levels/saturation and changes in muscle contraction and movement. Thus, our company's wearable device applications will provide the following:
- Better Versatility;
- Higher Medical Compliance;
- Faster Emergency Response;
- Health Monitoring; and
- a Sense of Community
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