Questions about your request or an order? Contact us
Systeme und Informatikanwendungen Nikisch GmbHsysGen GmbH - Am Hallacker 48 - 28327 Bremen - info@sysgen.de
Questions about your request or an order? Contact us
Cookie preferences
This website uses cookies, which are necessary for the technical operation of the website and are always set. Other cookies, which increase the comfort when using this website, are used for direct advertising or to facilitate interaction with other websites and social networks, are only set with your consent.
Configuration
Technically required
These cookies are necessary for the basic functions of the shop.
"Allow all cookies" cookie
"Decline all cookies" cookie
CSRF token
Cookie preferences
Currency change
Customer recognition
Customer-specific caching
Individual prices
Selected shop
Session
Comfort functions
These cookies are used to make the shopping experience even more appealing, for example for the recognition of the visitor.
The use of AI in healthcare can help many areas to work more efficiently and accurately. Examples include better diagnosis of diseases, development of personalized treatment plans and prediction of relapses, as well as analysis of medical images and reports.
Particularly noteworthy here is the possibility of analyzing large volumes of data to achieve better results in cancer research. Robotic assistance in surgical procedures or the monitoring of patients in their daily lives by networked devices are also examples of the use of AI in healthcare.
aI systems can also help improve the availability of healthcare services in rural areas and reduce healthcare costs. Overall, AI can help improve patients' lives and optimize the healthcare sector as a whole.
Medical IT departments are proving to be the biggest beneficiary here by using AI in operational processes, gaining insights from data, and making recommendations from AI-based analysis of that data. By using AI-based analysis, they can make recommendations and decisions based on the latest insights and trends. Particularly given the growing amount of data in hospitals and patients' increased expectations of their healthcare, implementing AI solutions is a sensible way to improve the efficiency and quality of medical care.
Virtualization enables health systems to provide services to physicians and patients across radiology departments and facilities. It enables the use of technology infrastructure in a more efficient manner and minimizes the need for dedicated GPU systems for each project. This increases the adoption of GPU-based AI applications and enables the use of AI to improve patient care. Virtualization thus provides the opportunity to deliver healthcare on a larger scale and more efficiently.
Key challenges
Before AI can be used in healthcare, there are still some challenges to overcome, both ethical and legal. One of the biggest challenges is the fragmented healthcare IT landscape, which often makes it difficult to merge and use data from different systems. Proper protection of patient data and an open and interoperable system that allows scalable data integration are critical.
However, AI can only reach its full potential if it has access to large volumes of cleansed and structured data. To fully realize this potential, it is important that clinical teams, physicians, clinicians, data scientists and other experts work closely together.
By taking full advantage of the capabilities of AI, medical IT departments can increase operational efficiency and create value from the vast amounts of data that exist in hospital information systems. AI-powered solutions make it possible to turn data into meaningful information and enable comprehensive integrated healthcare with more accurate prognoses and targeted therapies.
RISK
It can be difficult to integrate AI solutions into existing systems, as it requires extensive knowledge of tools and technologies, as well as understanding of existing data sources and structures.
PERFORMANCE
High performance is critical for AI, machine learning, and data analytics workloads, as these applications must process large amounts of data and perform complex calculations. Fast deployment is also critical to reap the benefits of AI as quickly as possible and increase the speed of decisions and processes. This includes the availability of sufficient resources such as memory, CPU and GPU power to perform the computations and analytics.
Scaling
Deploying AI in the enterprise requires effective scaling to ensure that resources are used efficiently and infrastructure costs can be managed. A key component of this is the manageability and availability of the infrastructure to ensure that the applications and the processes built on top of them are available and performing at all times. This requires careful planning and choosing the right technologies and tools that meet the needs of the business while being flexible and scalable.
There are already a number of promising solutions for the use of artificial intelligence in healthcare. We will present some of these in this blog post. NVIDIA-based solutions in particular are proving to be very effective and promising here, but it is important to keep an eye on the costs of the infrastructure to ensure that the investment in AI is profitable and that the company is able to take full advantage of AI.
Standardization of AI applications in healthcare
Core AI applications and frameworks include three main components designed to accelerate data analysis and diagnosis, and simplify the delivery and organization of medical data. Achieving these objectives helps reduce costs, increase efficiency and quality in healthcare, and enable patient-friendly healthcare.
Clinical and business health applications.
AI applications in healthcare facilitate the documentation of patient data, the storage and sharing of medical images, and the analysis of patient data in 3D representations, which increases diagnostic and therapeutic precision and improves collaboration between physicians. Core healthcare applications include EMR, picture archiving and communication systems (PACS) as well as advanced visualization solutions.
Data science research in health care.
For example, use NVIDIA Clara™ and MONAI, for AI application development and deployment: -NVIDIA Clara™ is a healthcare application framework for AI-powered imaging, genomics, and smart sensor development and deployment. -Clara™ Imagingis a medical imaging and pathology application framework. - Clara™ Guardian is a framework for intelligent hospital applications consisting of the NVIDIA DeepStream Toolkit for video analytics, the NVIDIA Riva SDK for conversational AI, and the NVIDIA Triton™ Inference Server for large-scale AI model deployment. -Clara™ Holoscan is a real-time AI computing platform for medical devices that enables rapid development and production of new devices that deliver AI applications directly to the operating room. - NVIDIA MONAI is a set of freely available open source frameworks for accelerating medical imaging research and clinical collaboration.
Emerging AI applications in healthcare.
AI applications in healthcare improve triage, diagnosis, and surgical insights by automatically analyzing and diagnosing medical images, triaging patients, and creating personalized treatment plans. They can also increase the precision and safety of surgical procedures.
ToP News from the NVIDIA GTC
Development of digital twins for medical devices
The digital twins created with NVIDIA Omniverse can accurately model hospital environments, medical instruments, and patients anatomically. Developers can use them to create AI-powered solutions, such as in neurosurgery, to reduce the duration of surgery and the time the patient spends under anesthesia. With the IGX platform optimized for AI processing and visualization, the alignment of surgical instruments can be automatically tracked to improve the efficiency of the procedure. With Clara Holoscan and IGX, you can develop, test and deploy, all on one platform.
Betrieb von NVIDIA-zertifizierten Unternehmenssystemen mit Arm-CPUs
Arm-basierte Systeme sind für Edge-Anwendungen weit verbreitet. Sie werden bereits in großem Umfang von großen Cloud-Service-Providern eingesetzt und werden auch für Anwendungen in Rechenzentren immer beliebter. Systeme, die auf der Arm-Architektur basieren, sind in der Lage, viele Kerne mit hoher Energieeffizienz zu betreiben und gleichzeitig eine hohe Speicherbandbreite und geringe Latenzzeiten zu bieten.
Da sich die Arm-Architektur in Rechenzentren immer mehr durchsetzt, wird es wichtig sein, optimal konfigurierte Systeme zu wählen. Dies gilt insbesondere für Arm-Systeme, die mit GPUs und Hochgeschwindigkeitsnetzwerken ausgestattet sind. Ampere Altra Prozessoren, die auf der Arm-Architektur basieren, konkurrieren mit der x86-Plattform, indem sie mehr Kerne zur Bewältigung rechenintensiver Workloads haben. GIGABYTE Server mit Ampere-CPUs bieten Verbesserungen bei den Gesamtbetriebskosten (TCO), da sie pro Kern effizienter und zu einem niedrigeren Preis pro Kern arbeiten. 1U- und 2U-Server verfügen über einen Ampere Altra-Prozessor mit einem Sockel und 128 PCIe (Gen4)-Lanes sowie Unterstützung für alle High-End-RAM-Konfigurationen.
Das erste NVIDIA-zertifizierte Arm-System ist der GIGABYTE G242-P33 Server, das mit dem Neoverse-basierten Ampere Altra Prozessor und bis zu vier NVIDIA A100 Tensor Core GPUs ausgestattet ist.
New AI applications and workflows
Open source AI innovation for healthcare continues with MONAI v1.0
The lifecycle of medical AI includes labeling data, training models, developing and optimizing AI applications, and finally deploying and monitoring these applications in clinical production. The MONAI project has a variety of tools to help researchers and data scientists label data and quickly train powerful models. MONAI v1.0 offers numerous new features, including MONAI Model Zoo, auto-3D segmentation, and active learning in MONAI Label.
Ultra-high frame rates for AI medical devices with the Clara Holoscan SDK
To integrate real-time AI capabilities into medical devices, developers need pipelines that enable low-latency processing of combined sensor data from multiple channels. The NVIDIA Clara Holoscan SDK v0.3 now enables an ultra-fast frame rate of 240 Hz for 4K video data, allowing developers to combine data from more sensors and create AI applications for surgical support.
Democratizing and accelerating genome sequencing analysis with Clara Parabricks v4.0
Clara Parabricks v4.0 offers significant improvements in the delivery and scaling of genome sequencing pipelines for genomic researchers and bioinformaticians. It is currently free to researchers, can be deployed on the Broad Institute's Terra SaaS platform, and is available through other cloud providers and partners.
Deploying AI models at scale with an operating system for smart hospitals
Monai is a useful resource for developers looking to create and implement AI models for medical image analysis, as it provides them with an easy way to perform data preparation, automate model development, and run models on multiple platforms.
Potentials through the use of AI
Based on prognostic data, healthcare providers could take preventive measures, reduce health risks and avoid unnecessary expenses. This helps to increase quality and minimize health risks on the patient side and, on the other hand, to increase operational performance and efficiency while avoiding unnecessary expenditures.
Increase operational performance and efficiency
Using AI-based solutions to filter information from data as needed can be supportive, both in terms of cost and time.
Fields of application:
Planning
Information retrieval from findings
Cataloging of data
Analysis of medical data
Quality improvement and support for clinical decision making
AI-powered solutions can aggregate large volumes of health data that provide insight into a patient's health status, facilitating the decision-making process for healthcare providers, shortening time to diagnosis, optimizing therapy, and thus improving patient care.
Benefits:
Improvement in patient care
savings in therapy costs
Reduction of unnecessary expenditures through preventive measures
Using AI for preventive measures in common diseases such as heart disease, lung disease and cancer can be rewarding, both for the patient and for the healthcare system. AI enables predictions based on data from images, clinical data, medical history data and genomic information combined to form an overall picture. These predictions make it easier for physicians to select the most appropriate treatment and foresee complications.
Patient-friendly provision of data, diagnoses and reports
Until now, patients had to provide the information relevant for diagnosis to the medical professionals in person, be it X-rays, test results or other relevant health data, as well as in conversation, of course. This is time-consuming for both the patient and the medical professionals. The use of AI-based solutions or AI-supported healthcare services can create real added value here.
Fields of application:
Appointment bookings
Pre-transmission of relevant data
Request and retrieval of relevant results
NVIDIA AI EnterPRISE
NVIDIA & VMWare - "AI Enterprise" for Healthcare
NVIDIA AI Enterprise in conjunction with VMware can be used in healthcare for a variety of applications. Some examples are:
Medical imaging: NVIDIA Clara Framework can be used to analyze medical images and automatically generate diagnostic results. Through integration with VMware, medical images can be quickly and securely integrated into existing IT infrastructures.
Clinical Decision Support: NVIDIA Merlin Framework can be used to analyze patient data and generate recommendations for treatments and tests. Through integration with VMware, these recommendations can be incorporated into electronic health records to help physicians diagnose and treat patients more quickly and accurately.
Speech AI: NVIDIA RIVA Framework can be used to understand and interpret natural language processes. Through integration with VMware, it can be incorporated into applications such as patient voice assistants or medical dictation software to improve communication between physicians, patients, and other medical professionals.
Automated document capture: NVIDIA AI Enterprise can be used to automatically extract patient data from paper documents and insert it into electronic patient records. Through integration with VMware, this data can be integrated with existing IT systems to increase the efficiency and accuracy of patient data capture.
Overall, NVIDIA AI Enterprise, in conjunction with VMware, enables healthcare to integrate AI capabilities into existing IT infrastructures to enable more efficient and accurate diagnosis and treatment of patients.
NVIDIA AI Enterprise NVIDIA AI Enterprise is a software suite that lets enterprises realize the potential of AI without the need for AI expertise. It offers proven, open source AI frameworks and tools, supports applications with NVIDIA AI frameworks, is certified for enterprise data centers and public cloud, and includes enterprise-class NVIDIA support.
Key Technologies
To support your clinical applications: VMware vSphere with Tanzu
The digital transformation of healthcare has led to strong virtualization and AI penetration, reducing costs while improving security. The NVIDIA and VMware AI-Ready platform consists of the following building blocks:
Intelligent Hospitals with the AI Enterprise Ready Platform from NVIDIA and VMware provides end-to-end hardware and software that hospitals need for digital transformation. Developers, data scientists, and researchers can access the resources they need to efficiently develop and deploy AI applications, and IT administrators can provide uncompromised support with the tools and infrastructure they know. This comprehensive solution makes the intelligent hospital a reality and ultimately contributes to a better experience for physicians and patients.
Every step of the AI workflow is streamlined, from data preparation and training to inference and deployment. AI experts can train complex neural network models as well as tree-based models. Optimized for AI development and deployment, NVIDIA AI Enterprise includes proven, open-source containers and frameworks that facilitate the use of AI in the enterprise, such as speech AI, which is commonly used for automated customer support and digital sales reps, and computer vision for segmentation, classification, and recognition. Together with NVIDIA AI's flagship products, the NVIDIA H100 for mainstream servers and NVIDIA DGX systems, NVIDIA AI Enterprise makes AI accessible to any enterprise to develop cutting-edge AI workflows.
PRODUCTION-READY KI:
NVIDIA AI Enterprise, is essential for developing AI-powered medical imaging and genomics with NVIDIA Clara. NVIDIA AI Enterprise supports NVIDIA domain-specific frameworks that developers can leverage to build innovative business solutions.
Certified for use at any location:
Certified to run on mainstream NVIDIA-certified servers, with GPU acceleration or as a CPU-only solution, NVIDIA DGX systems, or in the public cloud, NVIDIA AI Enterprise can be deployed almost anywhere, enabling AI projects in today's increasingly hybrid data center. NVIDIA AI Enterprise is also suitable for running on popular virtualization and container orchestration platforms such as VMware vSphere with Tanzu and Red Hat OpenShift. This allows enterprise IT to integrate AI into the data center while relying on familiar tools and management solutions.
NVIDIA IGX
Advanced functional security for AI at the Edge
NVIDIA IGX is an industrial edge AI platform for high performance and advanced functional safety. Designed specifically for industrial and medical environments, NVIDIA IGX enables organizations to safely and securely deploy AI to support human-machine collaboration.
Intelligent machines complement the work of doctors, surgeons, and nurses in smart hospitals. AI can enable better treatment outcomes for patients. NVIDIA Clara™ Holoscan, running on NVIDIA IGX, provides real-time AI at the edge for hospitals. This enables developers to quickly bring the next generation of AI-enabled medical devices to market.
Editable editable, click me for edit, editable, click me for edit, editable, click me for edit ...
This could be a description of a product, maybe you want to have that but it will be shortend to a certain amount of characters ...
9.999,99 €*
NVIDIA certified systems
Deploying NVIDIA AI Enterprise at Scale
The NVIDIA AI Enterprise Software Suite is certified for use on NVIDIA-certified systems, including NVIDIA Ampere architecture-based GPUs, NVIDIA ConnectX SmartNICs, and NVIDIA BlueField DPUs. These systems offer Tensor Core technology to accelerate AI operations, as well as advanced networking, storage, and healthcare security capabilities. NVIDIA ConnectX SmartNICs and NVIDIA BlueField DPUs provide scalability, high performance, and secure infrastructure for any type of workload, from the cloud to the edge.
Mainstream Models from leading OEMs like Supermicro and Gigabyte
Zertifizierte Supermicro H100 Systeme der aktuellen GENERATION
NVIDIA H100 PCIe-Grafikprozessoren für Mainstream-Server werden mit der NVIDIA AI Enterprise Software ausgeliefert, die KI für nahezu jedes Unternehmen zugänglich macht und höchste Leistung in den Bereichen Training, Inferenz und Data-Science bietet. NVIDIA AI Enterprise in Verbindung mit NVIDIA H100 vereinfacht den Aufbau einer KI-kompatiblen Plattform, beschleunigt die KI-Entwicklung und -Bereitstellung mit Unterstützung auf Unternehmensebene und bietet die Leistung, Sicherheit und Skalierbarkeit, um schneller Erkenntnisse zu gewinnen und den Geschäftswert zu steigern.
Editable editable, click me for edit, editable, click me for edit, editable, click me for edit ...
This could be a description of a product, maybe you want to have that but it will be shortend to a certain amount of characters ...
9.999,99 €*
Your direct line to the experts at sysGen
sysGen supports healthcare facilities in digitizing their processes and infrastructure. We offer solutions in areas such as connectivity, digitization, cloud computing and security to improve the efficiency and quality of patient care. Our team of experts helps optimize data centers, implement cloud solutions and introduce innovative software. Contact us to learn more about our healthcare services and how we can help you digitize your facility.
This website uses cookies, which are necessary for the technical operation of the website and are always set. Other cookies, which increase the usability of this website, serve for direct advertising or simplify interaction with other websites and social networks, will only be used with your consent.
.jpg)
Product Name XYZ - Mostly Longer than short
