The rapid adoption of AI in medicine has introduced not only new technical possibilities but also heightened scrutiny from regulatory bodies responsible for clinical safety and effectiveness. Oversight from institutions such as the FDA and European authorities operating under the Medical Device Regulation (MDR) framework has transformed compliance into a structured, evidence-driven process rather than…
This interview analysis is sponsored by AcuityMD and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page. The MedTech commercial sector in 2026 is defined by a paradox of data. While research and development complexity…
Tenet Healthcare Corporation is one of the largest investor-owned healthcare services companies in the United States. Headquartered in Dallas, Texas, the company operates 65 acute care hospitals and over 450 healthcare facilities, including ambulatory surgery centers and other outpatient facilities. As of late 2025, Tenet reported trailing twelve-month revenue of approximately $20.8 billion, a…
However, the effectiveness of medical AI depends on a crucial element, i.e., accurately labeled, high-quality medical data. This is where an expert medical data annotation service provider steps in. What is medical data annotation? Medical data annotation is the process of accurately labeling healthcare data to make it worthwhile for AI training. This data can…
Bristol Myers Squibb is a global biopharmaceutical leader dedicated to delivering innovative medicines across oncology, hematology, immunology, cardiovascular disease, and neuroscience. The company serves patients worldwide through a comprehensive portfolio of breakthrough therapies developed across multiple therapeutic areas. In 2024, Bristol Myers Squibb reported annual revenue of $48.3 billion according to company earnings reports. At…
However, the ability of AI in the prevention and management of cardiovascular disease depends on the quality of cardiology datasets. Labeled data forms the backbone of imaging AI, shaping model performance, trustworthiness, and clinical applicability. High-quality labeled data enables AI models to deliver accurate diagnoses and reliable treatment recommendations. This piece explores how cardiovascular imaging…
Clinical trials comprise the most significant portion of drug development costs. In some cases, drug R&D costs can approach as high as $2 billion per drug and are accompanied by protracted timelines of 10-15 years. Pharmaceutical companies are turning to AI to shorten discovery timelines while dramatically upholding rigorous standards. AI-driven approaches have demonstrated meaningful…
Correctly identifying when a medical finding is absent rather than present is crucial when working on this specific task (for example, extracting labels from radiology reports using CV) about the presence or absence of prespecified pathologies. This article aims to highlight radiology data annotation from the perspective of a data annotation company, examining what goes…
This article delves deep into key aspects of data annotation for surgical AI models and explains why precisely labeled data are essential for safe and effective performance. What is surgical data annotation? Annotated data are foundational to training and improving artificial intelligence algorithms for minimally invasive surgery – including endoscopic, laparoscopic, and robotically assisted procedures…
One significant area that can help overcome this challenge is the integration of competent care intelligence and patient monitoring models. Virtual monitoring systems, which enable remote patient observation through audio-video devices, have enhanced safety, particularly for high-risk patients. Human oversight was necessary to develop this solution through continuous in-hospital patient audio-video (AV) monitoring. In this…