Advancements in artificial intelligence have brought about significant transformations in the medical field, particularly in surgical procedures. Surgeons seldom receive feedback on how well they perform surgery, despite evidence that it accelerates their acquisition of skills (e.g., suturing). Such feedback can be automated, in theory, by artificial intelligence systems. Surgical video annotation is a specialized application of data annotation in the medical field, where surgical procedures are meticulously analyzed and labeled in real time. It involves precise labeling of various elements an ..read more

Integrating artificial intelligence in surgical and endoscopic procedures has significantly revolutionized medical practices, enhancing diagnostic accuracy, surgical precision, and patient outcomes. Data Bridge Market Research analyses that the global surgical robots market, which was USD 4.4 billion in 2022, is expected to reach USD 16.54 billion by 2030. The success of these AI algorithms will rely heavily on the availability of high-quality annotated data to train these models effectively. Image and video annotation are critical for establishing ground truth in surgical data science endeavo ..read more

Data annotation in surgical AI for patient care is a crucial process that involves labeling and categorizing data to train and improve artificial intelligence algorithms. Specifically in surgical AI, data annotation typically refers to labeling medical images, videos, or other relevant data to create a supervised learning dataset for training AI models. Data annotation in Surgical AI improves patient outcomes by enhancing the accuracy, efficiency, and safety of surgical procedures that are automated or robot-assisted surgical procedures. Role of Data Annotation in Surgical AI Precise Diagnoses ..read more

Our Founder and CEO, Radha Basu, recently participated in the inaugural episode of the new TriNet original series “Leading with Passion” hosted by Pamela Rucker, a Professor at Harvard University. Radha, known for her visionary leadership and unwavering commitment to empowering communities, shared her inspiring story, from the early days of college to building iMerit and its present-day global prominence in the episode. Watch Session Early Days Battling Gender Gap The session touched on the challenges Radha encountered on her journey, how she drew inspiration along the way, and why humans w ..read more

The speed with which AI is advancing is undeniable. Every week, advancements in technologies such as computer vision, generative language AI, and robotics make headlines – promising more, better, and faster to the people and businesses that use them. In turn, the world of data annotation is advancing at a similar pace. As data hungry AI and ML models require higher quality to achieve better precision, annotation tools, experts, and people must be better equipped to meet the demand.  To meet this demand, data annotation technologies require automation to deliver better scale and speed thr ..read more

Healthcare AI is one of the most promising avenues in the healthcare sector and relies heavily on machine learning algorithms to analyze medical data to make predictions or assist in diagnosis and treatment decisions. It implies that data annotation is crucial in healthcare AI development and implementation. Diverse sources such as medical imaging devices, diagnosis documents, visual observations, and health data collection applications contribute to the vast influx of data into the healthcare industry. Whether visual (image-like) or textual form, this data serves various purposes, ranging fro ..read more

In today’s data-driven world, sensors are found in multiple applications like smartphones, autonomous vehicles, industrial control systems, and more, and sensor fusion is the technology behind this. Sensor fusion fuses data collected from various sensors for an accurate view of the condition, which is difficult to achieve with data from just one sensor.  Integrating data from multiple sensors is emerging as a game-changer across various industries. By combining data from sources such as 2D cameras, 3D LiDAR point clouds, radar, and more, the sensor fusion technology unlocks many possibili ..read more

Leading Autonomous Vehicle company was looking to build a highly precise, secure, and reliable system for the autonomous movement of vehicles while accurately interpreting information from multiple sensors, like navigation systems, vision modules, LiDAR, and Radar.  Successful development and maintenance of a robust 3D perception stack would offer accurate depth estimation, object detection, and scene representation for the company.  However, the performance of a 3D perception system depends on the quality of the available data and the associated labels and annotations. This company ..read more

The global Intelligent Document Processing market will reach USD 11.6 billion by 2030, according to a new report by Grand View Research, Inc. While organizations are grappling with managing ever-increasing volumes of documents, Intelligent Document Processing (IDP) has emerged as a powerful technology to enhance their efficiency and accuracy of data extraction and validation.  Intelligent Document Processing leverages advanced technologies such as artificial intelligence and machine learning to automate extraction, analysis, and data processing from various documents. It enhances efficien ..read more

The Intelligent Document Processing solutions market size was USD 1.2 billion in 2021 globally and will reach USD 1,452 million in 2022. Finance, insurance, law, healthcare, supply-chain management, or hospitality – no industry is untouched by the powerful effects of automated document data extraction. This transformative technology, powered by artificial intelligence and machine learning, enables contextual information to be extracted from documents, providing valuable insights.  By leveraging intelligent document processing (IDP), businesses can streamline their document processing work ..read more