Silexica provides software development tools reducing the time-to-market of software IP and intelligent products. Enabled by deep software analysis, heterogeneous hardware awareness, and quick design space exploration, the SLX programming tools accelerate the journey from software to application-specific hardware systems, democratizing accelerated computing. On June 10, 2021, Silexica was acquired by Xilinx. The terms of the transaction were not disclosed.
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Silexica has filed 1 patent.
Software optimization, Parallel computing, Instruction set architectures, Embedded systems, Microprocessors
Software optimization, Parallel computing, Instruction set architectures, Embedded systems, Microprocessors
Latest Silexica News
Nov 23, 2022
Lyon, FRANCE New York, Nov. 23, 2022 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Global Artificial Intelligence in Medical Diagnostics Market Size, Share & Industry Trends Analysis Report By Application, By End User, By Component, By Regional Outlook and Forecast, 2022 - 2028" - https://www.reportlinker.com/p06364328/?utm_source=GNW A range of patient care as well as intelligent health systems can be supported by artificial intelligence. For disease diagnosis, drug discovery, and patient risk assessment, artificial intelligence methods ranging from machine learning to deep learning are widely used in healthcare. Numerous medical data sources, such as magnetic resonance imaging, ultrasound, mammography, genomics, computed tomography scan, etc., are necessary to accurately identify diseases using artificial intelligence technology, such as MRI, mammography, genomics, CT scan, etc. Additionally, artificial intelligence primarily improved the infirmary experience and accelerated patients’ preparation to continue their recovery at home. Moreover, the application of artificial intelligence approaches also includes detecting a variety of diseases, including Alzheimer’s, cancer, diabetes, tuberculosis, chronic heart disease, stroke and cerebrovascular disease, hypertension, skin disease, and liver disease.AI in medical diagnostics includes AI services and software that aid healthcare practitioners in diagnosing various disorders. AI-based software systems can assess diagnostic process data and either assist with patient triage by identifying aberrant medical images or offer a suitable diagnosis to the healthcare practitioner. Deep learning, algorithms, and data insights are utilized by AI in medical diagnostics to diagnose life-threatening and crucial disorders. It automates the diagnostic process and reduces healthcare practitioners’ workload. COVID-19 Impact Analysis The COVID-19 pandemic significantly impacted a number of economies all over the world. Various businesses were demolished as a result of lockdowns imposed by governments all over the world. However, the AI in medical diagnosis market was positively impacted due to the emergence of the pandemic. The COVID-19 disease mostly affects sufferers’ lungs. Consequently, cardiothoracic imaging is a typical diagnostic procedure for determining the severity of the disease in COVID-19 patients. In 2020, the number of research projects employing AI approaches to diagnose COVID-19 increased dramatically. Numerous studies focused on summarizing the COVID-19 diagnosis from chest CT scans via AI technology. Multiple studies have demonstrated that AI models may be as precise as professional radiologists in diagnosing COVID-19. Market Growth Factor Increasing efforts of manufacturers on the development of human-aware AI technology The ultimate goals that were aimed during the formation of AI technologies were to make them more human-aware, which means constructing models with the features and characteristics of human cognition. In other words, the objective was to develop human-like AI. Additionally, a rise in human interference with AI techniques and an interest in discovering the process of machine learning has introduced new research challenges. These challenges include interpretation and presentation challenges, such as problems with automating components and intelligent control of crowdsourcing. Higher utilization of big data within the healthcare industry Big data, which refers to data that is both enormous and complicated, is generated at different points in the process of providing medical treatment as a result of the rising digitization and use of information technologies in the healthcare business. Big data in the field of medical diagnostics include, among other types of information and sources, readings from medical devices including sensors, healthcare claims, ECGs, X-rays, and other billing records; biometric data; and information generated from the web and social media interactions. Market Restraining Factor Medical practitioners’ reluctance to utilize AI-based technology Extensive progress in digital health has made it possible for healthcare providers to aid patients with novel treatment methods. AI technologies provide practitioners with tools that improve their ability to diagnose and successfully treat patients. However, doctors have been demonstrated to be resistant to adopting new technologies. For instance, medical professionals believe that AI would replace physicians in the coming years. Doctors and radiologists feel that talents, like empathy or persuasion, are uniquely human; hence, technologies cannot eliminate the requirement for a doctor entirely. Application Outlook By Application, the Artificial Intelligence in Medical Diagnostics Market is divided into In Vivo diagnostics (Specialty and Modality) and In Vitro diagnostics. In 2021, the in vivo diagnostics segment witnessed the biggest revenue share of the AI in medical diagnosis market. The rapidly rising growth of this segment can be ascribed to the increasing adoption of AI solutions by the healthcare and medical industries as these solutions aid to reduce human errors and enhance treatment efficacy. End User Outlook On the basis of End-User, the is segregated into Hospitals, Diagnostics Imaging Centers, Diagnostics Laboratories, and Others. In 2021, the diagnostic centers segment recorded a significant revenue share of the AI in the medical diagnosis market. In patients with infectious diseases and immunological disorders, laboratory tests are very helpful for verifying a diagnosis, estimating disease severity, and tracking disease progression. In disease management, timely diagnostic assessment and execution of trustworthy testing are crucial. Component Outlook Based on Component, the Artificial Intelligence in Medical Diagnostics Market is bifurcated into Software and Services. In 2021, the services segment acquired the largest revenue share of artificial intelligence in medical diagnosis. The high growth of the segment is attributed to the fact that the burden on healthcare practitioners is increasing at a very rapid pace, owing to which, they are increasingly outsourcing various services. Regional Outlook Region-Wise, the Artificial Intelligence in Medical Diagnostics Market is analyzed across North America, Europe, Asia-Pacific, and LAMEA. In 2021, North America accounted for the highest revenue share of the AI in medical diagnosis market. The growth of North American AI in the medical diagnostics market is primarily driven by technological advancements, an increasing number of fresh product approvals, an increasing adoption rate of artificial intelligence in healthcare, the presence of key market players, and an established IT infrastructure within the healthcare sector. The major strategies followed by the market participants are Product Launches. Based on the Analysis presented in the Cardinal matrix; Microsoft Corporation and Google LLC are the forerunners in the Artificial Intelligence (AI) in Medical Diagnostics Market. Companies such as Intel Corporation, Siemens Healthineers AG (Siemens AG), General Electric (GE) Co. (GE Healthcare) are some of the key innovators in Artificial Intelligence (AI) in Medical Diagnostics Market. The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Microsoft Corporation, Nvidia Corporation, IBM Corporation, Intel Corporation, Google LLC, Siemens Healthineers AG (Siemens AG), General Electric (GE) Co. (GE Healthcare), Xilinx, Inc., Digital Diagnostics, Inc. and InformAI, LLC Recent Strategies deployed in Artificial Intelligence (AI) in Medical Diagnostics Market Acquisitions and Mergers: Mar-2022: Microsoft acquired Nuance Communications, a leading conversational AI and ambient intelligence company. With this acquisition, the company aimed to aid healthcare providers to deliver more effective, affordable, and accessible healthcare to patients. In addition, the company would also help businesses in developing more customized and relevant customer experiences. Jun-2021: Xilinx acquired Silexica, a C/C++ programming and analysis tools provider. Through this acquisition, the company aimed to accelerate its migration from software to application-optimized hardware systems through the Software programmability capabilities of Silexica. In addition, this acquisition would also complement the prevailing Vitis solution along with its potential to reach a broader line of developers. Apr-2021: Siemens acquired Varian Medical Systems, an American radiation oncology treatment, and software manufacturer. Following this acquisition, Siemens would use Varian’s AI-assisted analytics in order to accelerate the development and distribution of redefined cancer diagnosis, data-driven precision care, as well as post-treatment survivorship. Aug-2020: Digital Diagnostics took over 3Derm Systems, a medical technology company. Following this acquisition, the company aimed to leverage 3Derm’s autonomous AI in order to enhance healthcare quality while mitigating suffering and costs. Partnerships, Collaborations and Mergers: Sep-2022: Microsoft entered into a partnership with Novo Nordisk, a leading global healthcare company. Following this partnership, the companies aimed to accelerate the discovery as well as the development of medication and drugs through the capabilities of AI and big data. May-2022: GE Healthcare signed an agreement with Alliance Medical, a radiology services company. Under this agreement, the companies aimed to develop a digital health solution by employing advanced AI and data analytics. In addition, this agreement would also incorporate tools that facilitate daily management while also offering problem-solving. Mar-2022: Digital Diagnostics partnered with Baxter International, an American multinational healthcare company. Following this partnership, the companies aimed to integrate Digital Diagnostics’ AI technology into Baxter devices in order to aid front-line care workers in providing high-quality care with enhanced care outcomes to patients. Nov-2021: GE Healthcare partnered with Optellum, a lung health company. This partnership aimed to expedite precision diagnosis along with lung cancer therapeutics through AI in order to aid healthcare providers in evaluating lung nodule malignancy along with suspicious lesions, such as cancerous or benign. Jun-2021: Siemens entered into a partnership with Prisma Health, a not-for-profit health organization. Under this partnership, the companies aimed to integrate the clinical expertise of Prisma into Siemens’s technology intending to redefine the future of health care. Jun-2020: Siemens partnered with Geisinger, a regional healthcare provider. This partnership aimed to expedite components of the strategic priorities of Geisinger with respect to constantly enhancing their care for communities and patients throughout the region. Product Launches and Product Expansions: Oct-2022: Google Cloud launched Medical Imaging Suite, a technology to help with the interoperability and accessibility of radiology. This product aimed to deliver flexible choices for cloud, edge, or on-premise deployment in order to enable businesses to comply with the diverse sovereignty, privacy, and security demands of customers. Sep-2022: GE Healthcare launched Optima IGS 320, an AI-powered Cath lab. With this launch, the company aimed to further boost cardiac care throughout India in order to propel intelligent imaging with the aim to support cardiologists as well as personalized treatment therapies and protocols. Furthermore, this launch would also accelerate the access of Indian patients to healthcare. Sep-2022: NVIDIA released the NVIDIA IGX, an industrial-grade edge AI platform. This solution aimed to offer highly secure and low-latency AI inference to help in fulfilling the demand for instant insights from a range of devices and sensors for medical applications. Jul-2022: GE Healthcare rolled out its 5G Innovation Lab in India. With this launch, the company aimed to increase patient’s access to high-quality care through 5G-enabled healthcare solutions, including Augmented & Virtual Reality, Artificial Intelligence, and Advanced Visualization. In addition, it would also streamline teleradiology and image transfers to entirely transform remote care. Mar-2022: Siemens introduced NAEOTOM Alpha and MAGNETOM Free.Star. Through this launch, the company aimed to strengthen its position within the clinical decision-making sector throughout the full healthcare spectrum. The MAGNETOM Free.Star encompasses the ability to expand patients’ access to high-value care. Furthermore, NAEOTOM Alpha offers high-resolution data images at minimal doses, enhanced contrast at lower noise, and spectral information in each scan. Mar-2022: NVIDIA rolled out Clara Holoscan MGX, a platform for the medical device sector. Through this launch, the company aimed to develop and install real-time AI applications at the edge, particularly manufactured to comply with regulatory standards. Nov-2021: IBM Watson rolled out the IBM Imaging AI Orchestrator, a cloud-based AI service. Following this launch, the company aimed to aid radiologists in managing their access to AI insights in terms of reading workflow. Furthermore, this solution would offer managed access to regulatory-cleared AI applications through the best-in-class AI solution providers to imaging businesses. May-2021: GE Healthcare unveiled Xeleris V, a virtual review and processing solution. This solution aimed to eliminate the requirement for a standalone nuclear medicine workstation, which would allow healthcare providers to securely access data from multiple locations. Nov-2020: GE Healthcare released the Edison Developer Program, a range of breakthrough imaging innovations. Through this launch, the company aimed to aid customers in redefining the future of healthcare by addressing the two-part challenge of the modern healthcare environment, including the delivery of high-quality care with higher capacity and workflow issues. Apr-2020: IBM unveiled AI-Powered Technologies. Through this launch, the company aimed to aid research and the health community in expediting medical treatments and insights discovery for COVID-19. Jan-2020: Microsoft introduced AI for Health, a five-year program of the company. This solution aimed to leverage AI capabilities in order to help businesses along with researchers in addressing major healthcare challenges throughout the world. Approvals and Trials: Apr-2020: Siemens received FDA approval for its AIDAN artificial intelligence technologies. This patient foundation-focused bed aimed to offer four new features viz. OncoFreeze AI, PET FAST Workflow, FlowMotion, and Multiparametric PET Suite AI. Scope of the Study
Silexica Frequently Asked Questions (FAQ)
When was Silexica founded?
Silexica was founded in 2014.
Where is Silexica's headquarters?
Silexica's headquarters is located at Lichtstrasse 25, Cologne.
What is Silexica's latest funding round?
Silexica's latest funding round is Acquired.
How much did Silexica raise?
Silexica raised a total of $26M.
Who are the investors of Silexica?
Investors of Silexica include Xilinx, Startup Autobahn, Horizon 2020, SquareOne, Seed Fonds Aachen and 5 more.
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