Hanyang University · 医学
Professor Jaehyuk Cha's research lab specializes in advancing artificial intelligence and machine learning for medical diagnostics, with a strong focus on early detection and classification of critical diseases using medical imaging. The lab develops innovative deep learning frameworks combined with explainable AI to improve accuracy in diagnosing skin cancer, diabetic retinopathy, COVID-19, and chest abnormalities from radiographs and retinal scans. A key emphasis is on addressing real-world clinical challenges such as data imbalance, low-contrast lesions, and model interpretability to enhance clinical usability and patient outcomes. The lab also explores AI-driven solutions for online healthcare prediction and assistive technologies for people with visual impairments.
Figures are computed from collected data and may differ slightly.
Skin cancer is a serious disease that affects people all over the world. Melanoma is an aggressive form of skin cancer, and early detection can significantly reduce human mortality. In the United States, approximately 97,610 new cases of melanoma will be diagnosed in 2023. However, challenges such as lesion irregularities, low-contrast lesions, intraclass color similarity, redundant features, and imbalanced datasets make improved recognition accuracy using computerized techniques extremely diffi
The competence of machine learning approaches to carry out clinical expertise tasks has recently gained a lot of attention, particularly in the field of medical-imaging examination. Among the most frequently used clinical-imaging modalities in the healthcare profession is chest radiography, which calls for prompt reporting of the existence of potential anomalies and illness diagnostics in images. Automated frameworks for the recognition of chest abnormalities employing X-rays are being introduce
The COVID-19 virus's rapid global spread has caused millions of illnesses and deaths. As a result, it has disastrous consequences for people's lives, public health, and the global economy. Clinical studies have revealed a link between the severity of COVID-19 cases and the amount of virus present in infected people's lungs. Imaging techniques such as computed tomography (CT) and chest x-rays can detect COVID-19 (CXR). Manual inspection of these images is a difficult process, so computerized tech
Diabetic retinopathy (DR) and diabetic macular edema (DME) are forms of eye illness caused by diabetes that affects the blood vessels in the eyes, with the ground occupied by lesions of varied extent determining the disease burden. This is among the most common cause of visual impairment in the working population. Various factors have been discovered to play an important role in a person's growth of this condition. Among the essential elements at the top of the list are anxiety and long-term dia
The rapid increase in Internet technology and machine-learning devices has opened up new avenues for online healthcare systems. Sometimes, getting medical assistance or healthcare advice online is easier to understand than getting it in person. For mild symptoms, people frequently feel reluctant to visit the hospital or a doctor; instead, they express their questions on numerous healthcare forums. However, predictions may not always be accurate, and there is no assurance that users will always r
Abstract The Internet of Things is emerging as a crucial technology in aiding humans and making their lives easier. Among the human population, a large percentage of people suffer from disabilities resulting in challenges in everyday life particularly people with visual disabilities. While several inventions exist to aid people with blindness in their everyday lives, the tools are not adequate in terms of accessibility and efficiency. Smart cane is a useful technology that is being researched an
The performance of human gait recognition (HGR) is affected by the partial obstruction of the human body caused by the limited field of view in video surveillance. The traditional method required the bounding box to recognize human gait in the video sequences accurately; however, it is a challenging and time-consuming approach. Due to important applications, such as biometrics and video surveillance, HGR has improved performance over the last half-decade. Based on the literature, the challenging
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