By: Pradeep Goel, Chief Executive Officer of Solve.Care - Technology Innovators" /> By: Pradeep Goel, Chief Executive Officer of Solve.Care - Technology Innovators" />
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The Future of Healthcare Lies in Decentralization

By: Pradeep Goel, Chief Executive Officer of Solve.Care

By: Pradeep Goel, Chief Executive Officer of Solve.Care

The Future of Healthcare Lies in Decentralization

The healthcare sector is one of the fastest growing industries worldwide and as such insurmountable efforts have been expended to adapt to the constant advances in technology and the needs of patient care. One of these advances that is quickly becoming the go to for new healthcare systems and solutions is blockchain. Blockchain technology has been helping to lead in the decentralization of almost every industry today. For the healthcare in particular, it can greatly streamline the administration, relationships and interactions among stakeholders, and management of logistics that health systems are built on and the overall quality of care they can provide.

The main aim of utilizing blockchain technology and decentralizing healthcare is to address the issues and problems affecting the industry. By putting patients at the center of their own healthcare journey, decentralizing the healthcare sector with the help of blockchain helps provide patients with the information, ownership, and control over their own healthcare data. This is achieved by decentralizing data into individual patient nodes. This is also useful in population health management as patients can easily provide consent for access to their health data to be shared for the creation of a shared archive of health information of any specific condition. It also allows the patient the ability to easily monetize parts of healthcare data. All this can be done anonymously, thus protecting their privacy.

It is well known that different healthcare organizations often keep fragmented records for patients, particularly when more than one organization is involved in the care. Blockchain can be used to help to eliminate this issue and ensure that there are no missing or fragmented records by creating a distributed electronic health record (EHR) ecosystem made up of individual patient nodes, where they have their complete health records. This will further help to ensure improved quality, eliminate repeated and expensive tests, reduce errors, which will provide financial and operational benefits to healthcare organizations.

Other than the aforementioned advantages of a decentralized healthcare sector with an increased concentration on the patient, the approach can be used to improve healthcare on a global scale. Blockchain frameworks will help support and strengthen disease surveillance systems in the case of outbreaks, organize research on a global scale, and even provide a consensus to what is the best method to combat specific diseases.

Blockchain technology is also immutable and traceable. This allows the user to pinpoint specific transactions or actions that have been taken, whether it be in the patient journey or when it comes to logistics of pharmaceuticals. It is the best way to minimize or even eliminate healthcare and pharmaceutical fraud and errors. Overall, blockchain and a decentralized healthcare sector is the next logical step towards a more efficient, patient focused, and better healthcare system.

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Composite AI provides an extra dimension for businesses looking for growth, compliance and profitability

Szymon Klarman; Knowledge Architect at BlackSwan Technologies

Szymon Klarman; Knowledge Architect at BlackSwan Technologies

Composite AI provides an extra dimension for businesses looking for growth, compliance and profitability

Single AI technologies are useful, but lack the added context, insight and edge that a combination of AI techniques can provide

While the first wave of digital transformation centered on the digitalization of business processes and offerings, including products, services, and experiences; artificial intelligence (AI) is driving the second wave, enabling organizations to take a more holistic approach to harnessing and analyzing data in order to further improve decision-making, staff productivity, and operational efficiency.

Enterprises have found AI techniques such as machine learning particularly valuable in deriving insights through data analytics, and are now going beyond to even more effectively harness their data by using machine learning in conjunction with other AI techniques and advanced technologies. This is essentially the emerging theme of Composite AI, which Gartner recently recognized under the ‘Innovation Trigger’ of its Hype Cycle for Artificial Intelligence, 2021. In the previous year, Gartner’s Hype Cycle of Emerging Technologies, 2020 report identified Composite AI as one of the top 30 technologies with the highest degree of predicted impact on business and society in the next several years. This was after evaluating 1,700 technologies.

Composite AI combines multiple AI techniques

Composite AI is a breakthrough approach that combines multiple AI techniques to efficiently solve a wider range of business problems by more deeply interpreting data. These AI techniques may include natural language processing, machine learning, and deep learning; and other advanced technologies such as knowledge graphs.

Knowledge graph technology contextualizes massive amounts of data in a way similar to the human mind, while relying on data management processes that involve a number of AI techniques to thoroughly interpret the data. As a live information asset, the technology builds a comprehensive representation of entities and all the relationships between them using conceptual maps. These graphs can be further enriched with structured and unstructured data from a variety of internal and external sources, such as social media and global news, to ensure that all relevant information is included. Knowledge graphs can also evolve over time to reflect the most up-to-date state of intelligence.

Natural language processing combines computational linguistics — rule-based modeling of human language — with other AI techniques such as machine learning and deep learning to analyze text written or words spoken by human beings. Thus, by converting human language into a machine-understandable format, natural language processing systems enable computers and humans to interact with each other.

Machine learning algorithms power self-learning models that learn how to make predictions based on historical sample data and automatically improve through experience. These algorithms are commonly used to classify information in order to understand the context. When combined with knowledge graph technology, machine learning algorithms can be used to continuously update the graph and create new knowledge about the objects and their relationships. Machine learning algorithms can also uncover non-obvious relationships between the entities then use that knowledge to categorize and organize the data.

While machine learning uses basic neural networks to solve problems involving structured data, deep learning algorithms leverage more complex neural networks to solve even more complicated problems involving either structured or unstructured data or both. When combined with multi-level semantic natural language processing, these AI technologies can break each article down to the sentence-level, resolving the nature of each entity and their respective actions.

All these technologies combine to help decision-makers gain insights of unprecedented granularity, depth, and precision by responding to queries with a representation of all relevant pieces of information in one consistent conceptual map. This overview of all data and relationships between them is particularly beneficial when making decisions within the realm of business challenges such as due diligence and compliance.

The democratization of AI has further fueled the widespread adoption of AI technologies, enabling users of all skill levels to develop intelligent business applications. This, in combination with Composite AI, has empowered business teams with augmented intelligence while minimizing the need for specialized data scientists and lengthy data integration projects. As a result, business teams are able to focus more on problems requiring higher levels of intellect and creativity.

Composite AI in action

Enterprises across various industries are already benefiting from the use of a Composite AI approach. In one such example, an insurance company uses multiple AI techniques to select the best coverage plan for a new customer.

Knowledge graph technology is first utilized to gather all relevant information about the prospective customer such as company overview, insurance history, relationships, and related news. The graph is further enriched with all relevant domain knowledge about the insurance plans available along with various criteria such as location, industry, and customer base.

The customer is analyzed to propose a path for the resolution of the case based on AI inference rules and graph analysis. Then, the system automatically initiates contact with a link to an AI-powered chatbot to negotiate an insurance proposal. The system also clarifies other relevant details with the customer to explore additional opportunities. If needed, the system will engage an account manager to work further with the customer. Finally, the system analyzes the outcome of the case to learn and automatically improve.

As organizations remain under constant pressure to maintain a competitive advantage in the face of the ever-growing threat of new players, AI will prevail as the key driver of digital transformation. Thus, to compete and thrive, organizations will have to adopt AI technologies while capitalizing on their vast amounts of historical data — an unfair advantage over newcomers. With Composite AI, organizations can go one step further by combining multiple AI techniques to maximize the strengths and minimize the weaknesses of each.

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Sleepme: The universal sleep coach

Tara Youngblood, Co-Founder and CEO, Sleepme Inc

Sleepme: The universal sleep coach

Tara Youngblood is the founder and CEO of Sleepme, a company that creates award winning technologies and apps that are changing the way world sleeps. A leading sleep authority, Tara has given a TEDx talk on the recipe for effective sleep. In addition, she has spoken for: National Sleep Foundation, Charlotte Science Museum, Wellness conferences and Health Optimization Summit. Tara is the sleep coach for the Cincinnati Reds and has consulted with the military and veteran groups. She speaks on an array of topics in an interview:

Conception of Sleepme

Sleepme is the premier sleep coaching site for finding all the tools and resources one needs to improve their sleep and restore their life. The company is also the parent company of the revolutionary sleep science brand Chilisleep (R), and its award-winning sleep solutions ChilPadTM and OOLER(R) products. Sleepme ranks no. 615 on the 2020 Inc. 5000 list. “Temperature is one of the first symptoms that appears in the course of any illness, disease or even metabolism change. As we age or even navigate hormonal changes, managing temperature is can be difficult. But it is the most difficult at night” observes Tara. She maintains that since temperature is tied to our circadian rhythm and sleep outcomes, managing the temperature in bed all night has become essential to maintaining healthy sleep outcomes. Fans and AC are not enough to allow the body to drop two degrees core temperature and so most people are not falling asleep quickly and staying asleep all night. “So, despite whatever else is going on, even shift work or weird sleep schedules, we enable a drug-free, temperature management on a scale that meaningfully impacts sleep for all individuals.”

Healthcare industry – Challenges galore

“Wellness and healthcare need to be addressed at home. Time and contagion have made in -office treatments difficult. If sleep, can be amazing, people heal faster, have fewer other symptoms and have the energy to tackle even the mental health side of wellness.”

Sleepme solutions

Sleep is the foundation to healing and wellness. Our bodies are designed to manage critical healing and health while sleeping. If we don’t get great sleep, consistently, over time it leads to ever disease of the elderly. “We offer easy, drug free solutions to create an ideal environment for the body to achieve great sleep, whenever you can get it and consistent enough to deliver improved symptoms, memory, will power and reduce further injury.”

Leadership traits

“Science driven solutions encompass the best experience for the individuals. Healthcare can get results but often doesn’t consider the compliance at home. We deliver easy, consistent sleep solutions that make diet, fitness, and healing easier.” Fear of failure, according to Tara, is failure as a stopping spot not part of an endless cycle of learning, growing and progressing. “The scientific method pushes us to test and iterate. If failure is a test we can learn from, then that failure means we have a new parameter for what not to do again. Businesses fail not from one event, or one decision but from a million variables.”

The success mantra

Healthcare is still ultimately about the people we serve, adds Tara. “They are the ones we serve even when all the other metrics are fighting for your attention. If you can’t have empathy for the human at the other end, if you don’t know the why you are doing what you are doing, then you will struggle in the moments of difficulty to rise above the current situation to continue your journey.”

Company: Sleepme Inc

Website: www.sleep.me

Management:  Tara Youngblood, Co-Founder and CEO

Founded Year: 2016

Headquarters: Mooresville, North Carolina

Description: Sleepme develops IoT-based sleeping products and a SaaS platform to improve people’s health and well-being.

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