AI Drives an All-in-One Medical Image Diagnosis System
|
By HospiMedica International staff writers Posted on 07 Jan 2019 |

Image: AI HUB, an AI medical all-in-one platform (Photo courtesy of JLK Inspection).
An innovative predictive medical image diagnosis platform has the ability to detect and monitor more than 30 medical conditions from 14 regions of the body with pinpoint accuracy.
The JLK Inspection (Seoul, Korea) AIHuB diagnostics platform is an on-site universal artificial intelligence (AI) system that allows physicians to diagnose disease from medical images in a faster, more accurate manner, all from the convenience of a single central core. AIHuB is focused on brain pathologies and diseases such as ischemic strokes, hemorrhagic strokes, brain aneurysms, and Alzheimer's disease, as well as lung cancer, prostate cancer, breast cancer, and coronary artery disease.
The AIHuB carries out digital pathology from diverse imaging modalities, including magnetic resonance imaging (MRI), computerized tomography (CT), X-ray, and breast mammography, providing an objective AI-based analysis in a simple format. Utilizing the user-friendly interface, the AIHuB platform can provide clinicians with high-quality medical management, efficient medical treatment, and transparent medical services that seamlessly connect with all other in-hospital systems, including neural network solvers and libraries.
“We are excited to show how we are able to assist users with quantitative analysis of their medical images at their own convenience,” said Won Tae Kim, CEO of JLK Inspection. “The ability to provide optimal diagnosis support based on deep learning technologies, unique algorithms and imaging procession techniques will be a great benefit to all patients, whether suffering from minor or major ailments.”
Most of medical information today is stored digitally, but image data, findings, lab values, digital patient records, and surgery reports are handled separately. Data integration into one unified framework can enable faster handling of medical information and lay the foundation for efficient interaction between different specialties, enabling more precise and personalized clinical decisions.
Related Links:
JLK Inspection
The JLK Inspection (Seoul, Korea) AIHuB diagnostics platform is an on-site universal artificial intelligence (AI) system that allows physicians to diagnose disease from medical images in a faster, more accurate manner, all from the convenience of a single central core. AIHuB is focused on brain pathologies and diseases such as ischemic strokes, hemorrhagic strokes, brain aneurysms, and Alzheimer's disease, as well as lung cancer, prostate cancer, breast cancer, and coronary artery disease.
The AIHuB carries out digital pathology from diverse imaging modalities, including magnetic resonance imaging (MRI), computerized tomography (CT), X-ray, and breast mammography, providing an objective AI-based analysis in a simple format. Utilizing the user-friendly interface, the AIHuB platform can provide clinicians with high-quality medical management, efficient medical treatment, and transparent medical services that seamlessly connect with all other in-hospital systems, including neural network solvers and libraries.
“We are excited to show how we are able to assist users with quantitative analysis of their medical images at their own convenience,” said Won Tae Kim, CEO of JLK Inspection. “The ability to provide optimal diagnosis support based on deep learning technologies, unique algorithms and imaging procession techniques will be a great benefit to all patients, whether suffering from minor or major ailments.”
Most of medical information today is stored digitally, but image data, findings, lab values, digital patient records, and surgery reports are handled separately. Data integration into one unified framework can enable faster handling of medical information and lay the foundation for efficient interaction between different specialties, enabling more precise and personalized clinical decisions.
Related Links:
JLK Inspection
Latest AI News
Channels
Critical Care
view channel
AI Models Identify Patient Groups at Risk of Being Mistreated in Hospital ED
Triage errors in emergency departments can have life-or-death consequences, but identifying the root causes behind these errors has long been a challenge. Now, a team of researchers has applied machine... Read more
CPR Guidelines Updated for Pediatric and Neonatal Emergency Care and Resuscitation
Cardiac arrest in infants and children remains a leading cause of pediatric emergencies, with more than 7,000 out-of-hospital and 20,000 in-hospital cardiac arrests occurring annually in the United States.... Read moreSurgical Techniques
view channel
Wireless Metamaterial Spinal Implants Can Feel, Heal and Communicate
Spinal fusion, a common surgery performed on nearly a million Americans each year, often requires repeated hospital visits and radiation exposure to monitor recovery. Traditional monitoring relies on X-rays... Read more
Major Study Examines Endoscopies that Fail to Detect Esophageal Cancer
Barrett’s esophagus—the only known precancerous condition for esophageal adenocarcinoma—develops when chronic acid reflux damages the esophageal lining. Endoscopies are typically used to monitor such patients... Read morePatient Care
view channel
Revolutionary Automatic IV-Line Flushing Device to Enhance Infusion Care
More than 80% of in-hospital patients receive intravenous (IV) therapy. Every dose of IV medicine delivered in a small volume (<250 mL) infusion bag should be followed by subsequent flushing to ensure... Read more
VR Training Tool Combats Contamination of Portable Medical Equipment
Healthcare-associated infections (HAIs) impact one in every 31 patients, cause nearly 100,000 deaths each year, and cost USD 28.4 billion in direct medical expenses. Notably, up to 75% of these infections... Read more
Portable Biosensor Platform to Reduce Hospital-Acquired Infections
Approximately 4 million patients in the European Union acquire healthcare-associated infections (HAIs) or nosocomial infections each year, with around 37,000 deaths directly resulting from these infections,... Read moreFirst-Of-Its-Kind Portable Germicidal Light Technology Disinfects High-Touch Clinical Surfaces in Seconds
Reducing healthcare-acquired infections (HAIs) remains a pressing issue within global healthcare systems. In the United States alone, 1.7 million patients contract HAIs annually, leading to approximately... Read moreHealth IT
view channel
Printable Molecule-Selective Nanoparticles Enable Mass Production of Wearable Biosensors
The future of medicine is likely to focus on the personalization of healthcare—understanding exactly what an individual requires and delivering the appropriate combination of nutrients, metabolites, and... Read moreBusiness
view channel
Philips and Masimo Partner to Advance Patient Monitoring Measurement Technologies
Royal Philips (Amsterdam, Netherlands) and Masimo (Irvine, California, USA) have renewed their multi-year strategic collaboration, combining Philips’ expertise in patient monitoring with Masimo’s noninvasive... Read more
B. Braun Acquires Digital Microsurgery Company True Digital Surgery
The high-end microsurgery market in neurosurgery, spine, and ENT is undergoing a significant transformation. Traditional analog microscopes are giving way to digital exoscopes, which provide improved visualization,... Read more
CMEF 2025 to Promote Holistic and High-Quality Development of Medical and Health Industry
The 92nd China International Medical Equipment Fair (CMEF 2025) Autumn Exhibition is scheduled to be held from September 26 to 29 at the China Import and Export Fair Complex (Canton Fair Complex) in Guangzhou.... Read more







