Search results for: 'spectrometry machine learning'

Digital Pathology encompasses the use of optmized pathology workstations, whole slide imaging, image analysis, image management, laboratory information management system, use of machine learning, data handling and storage. Pathology is one of the most important fields in medicine, as the service provides investigation and validation platform in lie...

Microbiome research is on the rise following technological advancements and significant cost reductions in microbiome analysis. Research has unlocked the potential of microbiome in medical use cases, yielding tremendous insights on its nature, interactions, and impact within a host and in an external environment. Advanced studies on the role of mic...

This edition of IT, Computing and Communications (ITCC) Technology Opportunity Engine (TOE) captures developments related to Hyper-Distributed Edge Cloud, Edge AI Orchestration, Edge IoT, Real Time Analytics, Marketplace, Application Risk, 5G Data Management, AI Voice, Private Network PaaS, No-Code Workflow Automation, Vision AI, Digital Learning a...

Biomarker Analytics has always been one of the most in-demand branches of science relevant to the process of drug discovery and development in the Pharmaceutical Industry. Over the years several advances have been made in the area of biomarker analytics with the aim to accelerate the drug development process. The use of AI-based technology can incr...

The growing global demand for sustainable and ethical food sources has led to significant advancements in alternative proteins. From plant-based proteins to cellular agriculture and novel fermentation techniques, researchers and industry pioneers are leveraging biotechnology, data analytics, and process optimization to enhance the efficiency and sc...

Traditional training environments face patient safety risks, resource constraints, and limited exposure to rare event scenarios. Additionally, physical simulations are costly, limiting accessibility (especially in resource-constrained settings). Current simulation models lack personalization, resulting in operational complexity for hospitals due to...

Insurtech risk assessment and analytics has grown because of the digitization of the insurance industry and the demand for online insurance products and secure data management. Companies in this segment leverage artificial intelligence (AI), machine learning (ML), and big data analytics to provide insurers with more accurate and actionable risk...

Synthetic data is data generated artificially based on data collected from real-world occurrences. It is artificially generated data in the form of text, tables, images, and videos, among others. Synthetic data generation will address the challenge of inefficient datasets and privacy concerns. Generated using algorithms, it enables organization...

AI has moved from being a standalone technology to a core building block that drives global business growth. Advancements in key AI technologies, such as machine learning, deep learning, natural language processing (NLP), and computer vision, are happening at an exponential pace, constantly unlocking new capabilities and applications. AI adoptio...