AI-based medical diagnostic solutions are rapidly transforming the healthcare market. AI technology has broadly entered the medical sector, and among its applications, the most widely commercialized and market-leading field is the analysis of medical images (including medical imaging data) using AI. In particular, image analysis such as CT, MRI, and X-ray traditionally involves subjective interpretation by medical professionals. Therefore, applying AI technology is well suited to improving diagnostic accuracy and ensuring greater objectivity in interpretation. As the technological potential of AI in this area has become evident, many companies are actively entering the market.
[Fig] Application Scope of AI Technology in the Medical Field
AI-based medical diagnostic technology primarily utilizes deep learning–based medical image analysis. It works by training deep learning models on medical image (imaging) data to determine the presence or absence of disease. When developing algorithms that interpret images to detect diseases, factors such as deep learning architecture (model structure) and parameter optimization must be carefully considered. In order to improve the accuracy of disease detection, large volumes of training data are required. However, a current limitation is that available training data are often restricted to specific diseases and concentrated on a relatively small number of conditions with sufficient datasets. Therefore, the goal of the AI-based medical diagnostic solution market is to improve diagnostic accuracy while achieving broader applicability across a wider range of diseases.
[Fig] Global Market Status and Forecast for AI-Based Medical Image Analysis (Unit: Billion USD)
Amid this technological turning point, Korean companies are also actively entering the market. KaiHealth Co., Ltd. (CEO: Hyeju Lim) successfully raised Pre-A funding after its AI-based infertility solution technology was recognized. KaiHealth’s AI infertility solution helps infertile couples select the optimal embryo during the IVF (in vitro fertilization) process to increase the chances of pregnancy. The company’s CEO, Hyejun Lee, is a fertility specialist obstetrician-gynecologist who developed a highly accurate algorithm based on extensive clinical experience and datasets from more than 20 hospitals. With this investment, the company plans to conduct domestic clinical trials to obtain medical device certification from the Korean Ministry of Food and Drug Safety (MFDS) and expand its solutions into areas such as infertility, pregnancy, and contraception.
[Fig] KaiHealth’s AI-Based Infertility Solution (Embryo Selection)
Another AI healthcare company, Medipixel Co., Ltd. (CEO: Kyoseok Song), successfully secured KRW 17 billion in Series B funding after its technology was recognized. Medipixel’s solution MPXA is an AI system that automatically identifies narrowed blood vessels (stenosis) in cardiovascular angiography images and quantitatively measures the degree of narrowing. A key feature of the solution is that the entire analysis process is fully automated and completed within 1–2 seconds, allowing it to assist physicians in real time during procedures such as stent insertion in the catheterization laboratory.
[Fig] Medipixel’s Cardiovascular Disease Diagnostic Solution “MPXA”
Another Korean company, Connective Co., Ltd. (CEO: Doohyun Noh), is also actively developing AI-based medical analysis technologies. Connective develops X-ray–based surgical robots and AI-based X-ray analysis solutions. In particular, the company’s solution analyzes X-ray images to assist in musculoskeletal diagnosis and enables the acquisition and learning of human anatomical information. Through this technology, Connective expects to increase the accuracy of its artificial joint surgical robot to approximately 95%.
[Fig] Connective’s AI-Based X-ray Joint Analysis Solution
The BLT Patent & Law Firm Research Center stated that “the AI-based medical diagnostic solution market is expected to experience dramatic growth, and technological changes in this field will present new opportunities for companies through related technology development.” The Center also noted that “securing intellectual property rights related to medical image diagnostic technologies will be a strong strategic approach.”
As of 2024, BLT Patent & Law Firm has been selected as a partner by more than 2,000 innovative startups, supporting corporate growth and success through IP acquisition, strategic planning, investment attraction, and IP-based business support such as technology-special listings.
#AIMedicalDiagnosis #MedicalDeepLearning #AIDiagnosticSolutions #KaiHealth #Medipixel #Connective
AI-based medical diagnostic solutions are rapidly transforming the healthcare market. AI technology has broadly entered the medical sector, and among its applications, the most widely commercialized and market-leading field is the analysis of medical images (including medical imaging data) using AI. In particular, image analysis such as CT, MRI, and X-ray traditionally involves subjective interpretation by medical professionals. Therefore, applying AI technology is well suited to improving diagnostic accuracy and ensuring greater objectivity in interpretation. As the technological potential of AI in this area has become evident, many companies are actively entering the market.
[Fig] Application Scope of AI Technology in the Medical Field
AI-based medical diagnostic technology primarily utilizes deep learning–based medical image analysis. It works by training deep learning models on medical image (imaging) data to determine the presence or absence of disease. When developing algorithms that interpret images to detect diseases, factors such as deep learning architecture (model structure) and parameter optimization must be carefully considered. In order to improve the accuracy of disease detection, large volumes of training data are required. However, a current limitation is that available training data are often restricted to specific diseases and concentrated on a relatively small number of conditions with sufficient datasets. Therefore, the goal of the AI-based medical diagnostic solution market is to improve diagnostic accuracy while achieving broader applicability across a wider range of diseases.
[Fig] Global Market Status and Forecast for AI-Based Medical Image Analysis (Unit: Billion USD)
Amid this technological turning point, Korean companies are also actively entering the market. KaiHealth Co., Ltd. (CEO: Hyeju Lim) successfully raised Pre-A funding after its AI-based infertility solution technology was recognized. KaiHealth’s AI infertility solution helps infertile couples select the optimal embryo during the IVF (in vitro fertilization) process to increase the chances of pregnancy. The company’s CEO, Hyejun Lee, is a fertility specialist obstetrician-gynecologist who developed a highly accurate algorithm based on extensive clinical experience and datasets from more than 20 hospitals. With this investment, the company plans to conduct domestic clinical trials to obtain medical device certification from the Korean Ministry of Food and Drug Safety (MFDS) and expand its solutions into areas such as infertility, pregnancy, and contraception.
[Fig] KaiHealth’s AI-Based Infertility Solution (Embryo Selection)
Another AI healthcare company, Medipixel Co., Ltd. (CEO: Kyoseok Song), successfully secured KRW 17 billion in Series B funding after its technology was recognized. Medipixel’s solution MPXA is an AI system that automatically identifies narrowed blood vessels (stenosis) in cardiovascular angiography images and quantitatively measures the degree of narrowing. A key feature of the solution is that the entire analysis process is fully automated and completed within 1–2 seconds, allowing it to assist physicians in real time during procedures such as stent insertion in the catheterization laboratory.
[Fig] Medipixel’s Cardiovascular Disease Diagnostic Solution “MPXA”
Another Korean company, Connective Co., Ltd. (CEO: Doohyun Noh), is also actively developing AI-based medical analysis technologies. Connective develops X-ray–based surgical robots and AI-based X-ray analysis solutions. In particular, the company’s solution analyzes X-ray images to assist in musculoskeletal diagnosis and enables the acquisition and learning of human anatomical information. Through this technology, Connective expects to increase the accuracy of its artificial joint surgical robot to approximately 95%.
[Fig] Connective’s AI-Based X-ray Joint Analysis Solution
The BLT Patent & Law Firm Research Center stated that “the AI-based medical diagnostic solution market is expected to experience dramatic growth, and technological changes in this field will present new opportunities for companies through related technology development.” The Center also noted that “securing intellectual property rights related to medical image diagnostic technologies will be a strong strategic approach.”
As of 2024, BLT Patent & Law Firm has been selected as a partner by more than 2,000 innovative startups, supporting corporate growth and success through IP acquisition, strategic planning, investment attraction, and IP-based business support such as technology-special listings.
#AIMedicalDiagnosis #MedicalDeepLearning #AIDiagnosticSolutions #KaiHealth #Medipixel #Connective