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DNAMIC helps you define, implement, and optimize a robust data strategy tailored to your business needs. Our experts integrate Databricks solutions to provide centralized data processing, ensure governance, and maintain compliance with industry regulations.
DNAMIC delivers advanced AI and machine learning solutions to help businesses harness predictive analytics and automation. From fraud detection to predictive maintenance, we build models that transform data into powerful business tools.
With expertise in Databricks, DNAMIC architects scalable data systems that support real-time data processing, cloud migration, and integration across various data sources. We empower businesses with data solutions that grow with them.
DNAMIC delivers advanced AI and machine learning solutions to help businesses harness predictive analytics and automation. From fraud detection to predictive maintenance, we build models that transform data into powerful business tools.
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In this case study, you will see how we polished and supported this business to become its current video authority and provide its customers with a world-class user experience!
Through a partnership that has lasted more than five years, we expanded CLMA’s core and increased functionality, resulting in a broadened service catalog for their end-users.
We create User Experiences for each specific client goal. Find out how improved UX/UI has made CSS more influential in their market.
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Data Needs
Our overall health heavily depends on what we eat, how we care for our bodies and, ultimately, technology.
Although I pursued a career in software engineering and later started my own firm that provided data and AI services, my educational path initially began in medical school, where I received direct knowledge of the healthcare industry. This unusual path allowed me to gain a strong understanding of the developing data needs in healthcare.
A few decades ago, surgery rooms were somewhat of a mechanical service, characterized by a reliance on manual processes, limited technology and isolated data. Surgeons and medical staff primarily depended on physical records, basic monitoring equipment and their own expertise to perform procedures. The concept of gathering comprehensive data, interconnecting information and leveraging digital technology for surgical intelligence was virtually non-existent. Needless to say, the evolution of health procedures was condemned to very limited progress.
The absence of sophisticated tools frequently resulted in inefficiencies, extended recovery periods and an elevated risk of complications, despite the dedication and expertise of healthcare professionals.
Machine learning and artificial intelligence have transformed healthcare by providing predictive analytics, automated decision making and tailored therapy. In surgery rooms, these technologies are crucial for improving surgical precision, managing scheduling and predicting patient outcomes.
Predictive analytics forecasts future events by combining historical data with machine learning algorithms. Predictive analytics in surgery rooms can help identify probable issues, optimize resource allocation and enhance patient outcomes.
The integration of data from various sources, including robotic surgery systems and wearable devices, provides a comprehensive view of surgical performance and patient health. This holistic approach enables continuous improvement and personalized care.
AI-powered surgical assistance provides real-time data insights and recommendations, supporting surgeons in making informed decisions during complex procedures. This technology can help enhance the success rate of surgeries and reduce the risk of complications.
The application of big data, data warehouses, data lakes, ML and AI extends beyond clinical outcomes to operational efficiency and cost savings. By optimizing surgical schedules, inventory management and resource allocation, healthcare institutions can achieve improved financial benefits.
Real-time monitoring and alert systems provide immediate feedback and support during surgical procedures, improving patient safety and outcomes.
While the advantages of new technologies in the healthcare arena might be obvious to many of us, the path to implementing these technologies is not that straightforward from a legal and privacy point of view.
AI and data-related technologies in healthcare face significant challenges in navigating the complex landscape of global privacy laws and regulations designed to protect patients’ information on electronic medical records. With stringent frameworks like the GDPR in the European Union, HIPAA in the United States, PIPEDA in Canada and various national data protection laws in the Asia-Pacific region, these technologies must ensure robust compliance mechanisms to safeguard sensitive health data. These regulations mandate rigorous standards for data security, patient consent and the confidentiality of health information, making it imperative for AI systems to incorporate sophisticated privacy-preserving techniques.
The necessity to balance innovation in data processing and analysis with stringent legal and ethical obligations complicates the integration and scalability of AI in healthcare, often requiring a fine-tuned approach to ensure both technological advancement and adherence to global privacy standards.
Transitioning from outdated and mechanical surgical rooms to the advanced high-tech facilities of today has been a challenging process. Like many complex problems, there is no single solution but rather a combination of approaches and ongoing progress. The integration of data, data warehouses, data lakes, machine learning, artificial intelligence and predictive analytics has significantly transformed the healthcare field, particularly in surgical environments.
As we move towards a future that is increasingly cloud-connected, I believe that effective collaboration with private entities and the establishment of clear regulations for intelligent data processing will lead to significant advancements that benefit the entire population.
Written on Forbes by
Arturo García is the CEO of DNAMIC – Specialists in Databricks Data Solutions.
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