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The amazing journey of computer-aided testing: How did it move from the laboratory in the 1950s to the hospital?
In contemporary medicine, computer-aided detection technology (CADe) is undoubtedly an important tool to improve diagnosis and help doctors improve the efficiency and accuracy of medical services. The technology dates back to the 1950s, but advances in computing power and algorithms have expanded its applications, changing the face of medical diagnostics.
Computer-aided detection, or computer-aided diagnosis, provides doctors with excellent tools for interpreting medical images. Whether it is X-ray, MRI, endoscopy, or ultrasonic diagnostic technology, the image data generated must be carefully analyzed by professional medical personnel. In a short period of time, they need to comb through the ever-increasing amount of information to extract key health information, which is exactly the strength of the CADe system.
CADe systems process digital images or videos to support medical decision making by marking significant abnormal structures.
CAD systems have become more sophisticated over time and can now automatically identify a variety of lesions, including tumors. For example, many cancer screening centers have applied it to mammography, colon endoscopy, and lung cancer detection to enhance diagnostic accuracy.
From the laboratory in the 1950s to clinical application
As early as the late 1950s, the advent of modern computers prompted researchers in many fields to explore the possibilities of computer-assisted medical diagnostic systems. Initially CAD systems primarily used flow charts, statistical pattern matching, and knowledge bases to drive their decision-making processes. By the 1970s, some of the earliest CAD systems began to appear, often referred to as "medical expert systems." The development of these systems not only promoted education, but also laid the foundation for future CAD systems.
As CAD evolved, researchers gradually realized the limitations of these early systems and began using more advanced data mining methods.
In the 1980s and 1990s, the emergence of data mining methods enabled CAD systems to become more flexible and efficient. In 1998, the U.S. Food and Drug Administration (FDA) approved the launch of the first commercial mammography CAD system, ImageChecker, which officially brought CAD systems into clinical use.
Technology evolution and challenges
CAD systems operate on the basis of highly sophisticated pattern recognition technology. By scanning large amounts of medical images, the system can identify suspicious structures and mark them out. However, this technology still faces many challenges, especially in terms of input data, processing and evaluation systems.
Although the CAD system can improve the detection rate of lesions, it cannot achieve a 100% detection rate and may result in false positives (FP).
Currently, researchers are looking for a new generation of algorithms to address the poor performance of CAD systems in scenarios such as multiple diseases. Additionally, the effective design and implementation of electronic health records (EHR) is critical to the success of a CAD system.
Current Application Status
Currently, CAD technology is widely used in the diagnosis of breast cancer, lung cancer, colon cancer, diabetic retinopathy and many other diseases. Especially in mammography, CAD systems can assist doctors in identifying benign and malignant tumors, and in lung cancer screening, video synthesis CAD systems are considered to be valuable auxiliary tools.
Through these systems, medical professionals can make more informed diagnostic decisions and improve the quality of life for their patients.
However, some studies have pointed out that while CAD systems can improve disease detection rates, they may also increase the risk of false positives. For this reason, more and more hospitals are gradually adopting emerging technologies, such as deep learning and machine learning, to more effectively combine the advantages of CAD systems and overcome their original shortcomings.
Looking to the future
Looking into the future, CAD systems are expected to continue to expand their applications in areas such as digital pathology and image analysis. Although the development of technology faces challenges, such as data processing capabilities and algorithm performance, future trends will undoubtedly further integrate CAD systems into daily medical diagnosis.
Computer-aided testing has been developed for more than 40 years, and the potential of combining the medical field with technology continues to be released. With the advancement of technology, will it be possible to further improve human health and well-being in future medical treatment?
