Artificial intelligence (AI) technologies is shaping a new consumer-centric ecosystem connecting pharma, research and development, biotechnology, genomic, agri-science, health, and other life science industries. It brings together a world-class research team in life sciences with chemists, bioinformists, and data scientists creating innovations in computational biology, data mining, and parallel computing.
ICURO is investing in research and access to high performance computing, data management, high performance storage to deliver a rich breadth and depth of solutions. Through partnerships with leading companies and institutions around the world, we help accelerate scientific discovery in the age of genome and create value for health care, in the form of new drugs and treatments for disease.
The Explainable Artificial Intelligence (XAI) system focuses on the effectiveness of AI based on its ability ‘to explain’ decisions. We are extending this ‘ability to explain’ to deliver exceptional research capabilities for drug discovery with computational biology faster and more accurate insights. XAI framework drives clinical pathways based on machine learning algorithms trained on enormous amounts of data, validated protocols supported by evidence-based learning, and meaningful after-action reasoning. This enables a healthcare ecosystem at affordable costs, care collaboration and a better physician-patient relationship, and patient convenience which contributes to an effective and affordable healthcare system.
The research simulator platform focuses on a number of problems surrounding computational molecular biology and, in this context, a number of advanced machine learning algorithms and tools have been developed to tackle a wide collection of tasks. These include but are not limited to pattern and association discovery in event streams such as DNA, proteins, gene and the expression time series, etc., homology searching in protein and DNA databases, multiple sequence alignment, text mining in biological databases of both structured and unstructured, functional and structural characterization of proteins directly from sequence, and many more.
The AI system includes a tailored kit with wearable or portable medical devices for remote patient monitoring, and a smart phone or tablet app that integrates and seamlessly shares data from these devices to the clinician. The app is embedded with a virtual assistant, enabling AI-assisted pathways to enhance the overall user experience. All medical devices chosen are medical grade, noninvasive, senior-friendly, battery powered, and smart phone compatible. The explainable AI system enables the clinicians and care providers to review the health information in real time and request for an explanation for any generated patient guidelines, thereby validating the model using reinforcement learning techniques.
The intelligence care studio system merges science and consumer-friendly technology to redesign individualized care across the full lifecycle of the consumer and integrate it with healthcare delivery systems. It primarily facilitates real-time data collection using medical-grade devices and instant feedback, to deliver enhanced patient satisfaction. Consumer-friendly systems that monitor the sensors and devices and report the transition states of streaming data. Advanced data analytics is implemented for real-time risk assessment and outcome measures reporting. The key outcomes include patient-centricity, continuous care, preventive care, and affordable care.
The embedded AI system for smart medical devices provides an at-a-glance view of events, processes, and settings. It delivers predictions and trends, statistical summaries, and rates of alerts per observable parameter. The system is flexible to smoothly incorporate new components and features and existing components can be enhanced and replaced. The console permits management of every aspect of aggregation and distribution. A graphical user interface permits continuous and immediate visual reports of alerts, events and other user-selected events.
Artificial Intelligence (AI) Premium Member of NVIDIA, the global pioneer in accelerated computing in artificial intelligence and computer graphics transforming industries valued at more than $100 trillion, from gaming to healthcare to transportation, and profoundly impacting society. Engages in the design and manufacture of Graphics Processing Unit (GPU) segment consisting of product brands, including Tesla and DGX for AI data scientists and big data researchers, and GRID for cloud-based visual computing users.
As the AI Premium Member, ICURO has leverages NVIDIA DGX, a GPU-accelerated computational infrastructure to combine AI, data analytics, simulation, and visualization to support cross-disciplinary workflows in drug design and development. This platform enables researchers to apply high performance computing applications, pre-trained AI models and domain specific application frameworks in the areas of genomics, protein structure determination, virtual drug screening, medical imaging, and natural language processing.
Solution Partner of ThingWorx, a PTC business, the global leader with an unique portfolio of CAD, PLM, IoT, and AR technologies work together to create a powerful digital thread foundation that enables faster data continuity across your business for better collaboration between your teams. Companies from industries such as industrial equipment, high-tech, automotive, aerospace and defense, life sciences, and more use PTC’s best-in-class solutions to achieve their digital transformation goals and differentiate their business.
As a Solution Partner, ICURO has extended ThingWorx platform features with advanced machine learning techniques and connected research laboratory equipment in life sciences industry ranging from global biotech research institutions to pharmaceutical companies.
Artificial intelligence is a key next step in the evolution of life sciences companies and the future of health. AI-enabled applications, machine learning, and advanced analytics capabilities are already helping companies thrive and widening the gap between companies that embrace these technologies and those waiting for the future. Becoming an AI-fueled life science organization[…]
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There are many tasks AI can perform in the context of radiology. Some tasks will require just a medical image as input and will base the analysis purely on the pixels or voxels. Others will go one step further and will combine radiological images with information obtained from other sources. Combining medical images with other information can lead to insights that are not always easily to obtain for radiologists.[…]
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