Inha University Hospital Co., Ltd.

- Published clinical study on sleep apnea patients in the prestigious journal Digital Health - Clinical research on HoneyNaps SOMNUM validates its clinical efficacy BOSTON, Nov. 11, 2024 /PRNewswire/ -- Medical AI company HoneyNaps has published a paper demonstrating the clinical value and efficacy of its sleep disorder diagnostic algorithm, SOMNUM, in a leading international journal. According to the validation results, SOMNUM exhibited high sensitivity and specificity in interpreting apnea and hypopnea from polysomnography (PSG) across all groups of sleep-disordered breathing patients, with excellent predictive performance in mild, moderate, and severe sleep apnea cases. Continue Reading [Area under the receiver operating characteristic (ROC) curve of a deep learning algorithm model for predicting obstructive sleep apnea (OSA).] The study, titled "A Deep Learning Algorithm Model to Automatically Score and Grade Obstructive Sleep Apnea in Adult Polysomnography," was published in the latest issue of the SCIE-level international journal Digital Health (Volume 10: 1–13). The clinical study was conducted by Prof. Choi JiHo, Head of the Center for Sleep Medicine at SoonChunHyang University Hospital Bucheon, and Prof. Park MarnJoon of the Department of Otolaryngology at Inha University Hospital. It involved 1,000 adults diagnosed with various levels of sleep-disordered breathing through polysomnography, including simple snoring and mild, moderate and severe sleep apnea. Comparing data interpreted by the AI-based SOMNUM with expert readings of polysomnography, the study showed high sensitivity (95% CI: 98.06–98.51) and specificity (95% CI: 95.46–97.79) for detecting apnea and hypopnea across all sleep-disordered breathing groups. SOMNUM also demonstrated excellent predictive accuracy for sleep apnea across all severity levels. The AUC (area under the ROC curve) scores for disease prediction in mild, moderate, and severe groups were 0.9402, 0.9388 and 0.9442, respectively, with no significant differences among the groups. Sean Ha (Tae Kyoung Ha), the president of HoneyNaps USA Inc., "We are pleased that the clinical efficacy and efficiency of our sleep medical AI solutions are being validated through a reputable journal as well as through R&D and clinical trials, allowing steady adoption in medical settings. We will continue our research and development efforts and publish diverse study outcomes in global journals to validate the clinical value of HoneyNaps' medical AI technology." For further information, please contact: HoneyNaps USA, Inc. Christine Kwon / Managing Director Email: [email protected] Address: #517, SPACES, 361 Newbury Street, Boston, MA, 02115 Website: SOURCE HoneyNaps WANT YOUR COMPANY'S NEWS FEATURED ON PRNEWSWIRE.COM? 440k+ Newsrooms & Influencers 9k+ Digital Media Outlets 270k+ Journalists Opted In GET STARTED

"AI Assistant for Radiologists" Kakao Brain introduced last month a web-based radiology report Research Use Only (RUO) service powered by its large-scale artificial intelligence (AI), "KARA-CXR." Kakao Brain plans to expand the interactive functions supporting various imaging medical examinations through the advancement of large-scale multi-modal generation AI technology. SEOUL, South Korea, Feb. 22, 2024 /PRNewswire/ -- Kakao Brain has unveiled the research use only (RUO) web-based solution powered by "KARA-CXR" (short for "Kakao Brain AI for Radiology Assistant-CXR"), a large-scale AI algorithm that instantly generates preliminary radiology reports for doctor's review when chest X-ray images are uploaded onto the web. Through this user-friendly and seamless solution, medical researchers can experience various functions such as: receiving two types of AI interpretations of chest X-ray images together (a simple report and a detailed full report); ability to upload multiple DICOM files at once and receiving multiple reports simultaneously; and being able to share the AI interpretations within the research group or medical community. It also features compliant security measures that anonymize and protect any personal information contained in DICOM files. Kakao Brain started developing 'KARA-CXR' in 2022, collaborating with 11 leading university hospitals and large medical institutions. Partners include: Ewha Womans University Medical Center (Seoul, Mok-dong), Ajou University Hospital, Soonchunhyang Medical Center (Cheonan, Gumi, Seoul), Chungnam National University Hospital, Chungbuk National University Hospital, Keimyung University Dongsan Medical Center, Inha University Hospital, Dongguk University Ilsan Hospital, among others. 'KARA-CXR' has analyzed over 16 million chest X-ray images and readings. KARA-CXR is built on Kakao Brain's healthcare-specialized large-scale generative AI model, and the research team is preparing to publish the results in influential academic journals. Kakao Brain is preparing to obtain the European Union certification and seek approval from the US FDA and Korean Ministry of Food and Drug Safety. Kakao Brain is committed to the expansion of AI-powered radiology solution to address the inefficiency in the existing interpretation and reporting process, a shortage of radiologists, and to unburden healthcare professionals from the increasing workload. As an RUO tool, KARA-CXR is currently available for research use only and is not intended to diagnose, treat, cure, or prevent any disease. Kim Il-doo, CEO of Kakao Brain, stated, "As KARA-CXR was developed using high-quality data and the latest technology involving large-scale learning and generative AI, I hope that it will eventually play a great role in enhancing the workflow for the radiologists, not to mention improving the efficiency of chest x-ray image interpretation." He also added, "We are planning to go beyond generating AI interpretations of chest X-rays by expanding the algorithms to include interactive functions that support a variety of medical imaging tests, by utilizing the advanced large-scale multi-modal generative AI technology." Kakao Brain is a Korea-based global AI technology company. Founded in 2017, Kakao Brain aims to develop AI technology that will change people's lifestyle and embraces the challenge of asking the 'Unthinkable Question' to spark innovation, allowing everyone to live better lives. Kakao Brain has developed numerous innovative AI technologies and services designed to enhance people's quality of life through continuous technological innovation. These include the large-scale language model KoGPT and the image generation model Karlo. Additionally, Kakao Brain contributes to the development of the AI technology community by releasing 'Coyo,' a dataset consisting of approximately 740 million images and text. More information about Kakao Brain can be found on their official website: . SOURCE Kakao Brain

SEOUL, South Korea, Sept. 18, 2023 /PRNewswire/ -- VUNO Inc., South Korean medical AI company announced that its AI-based cardiac arrest risk management system, VUNO Med®-DeepCARS™, has proven its clinical validity for the first time through a prospective study utilizing Real World Data(RWD). VUNO announced that the multicenter clinical study paper, which confirms the clinical validity of VUNO Med®-DeepCARS™ through its initial prospective research, has been published in "Critical Care," a leading international journal in intensive care medicine. Continue Reading VUNO Med®-DeepCARS™ is a medical AI device that analyzes four vital signs: respiratory rate, body temperature, blood pressure, and heart rate to predict cardiac arrest within 24 hours in general ward patients. It's Korea's first cardiac arrest prediction AI medical device and is recognized as a breakthrough device by the Korean Ministry of Food and Drug Safety(MFDS). In the study published in Critical Care, the VUNO research team conducted a multicenter study using patient data from general wards at four tertiary medical institutions: Seoul National University Hospital, Bundang Seoul National University Hospital, Inha University Hospital, and Dong-A University Hospital, each with varying sizes, locations, and medical environments. A total of 55,083 patients admitted to general wards in all participating institutions over three months, comparing the in-hospital cardiac arrest (IHCA) prediction accuracy, unexpected intensive care unit transfer (UIT) prediction accuracy, and false alarm rate of VUNO Med®-DeepCARS™ with existing high-risk patient prediction systems like NEWS (National Early Warning Score). The study found that the predictive performance of VUNO Med®-DeepCARS™ had an AUROC score of 0.869, outperforming traditional methods (NEWS 0.767, MEWS 0.756). The number of alarms per 1,000 beds was more than halved compared to the same sensitivity level, proving higher trustworthiness in the alarms leading to actual medical interventions. Furthermore, its effectiveness was apparent across varying patient ages, genders, and times of occurrence. In this study, VUNO Med®-DeepCARS™ displayed exceptional predictive abilities and adaptability in identifying high-risk patients, even in its first prospective research. It consistently performed at the same level as in previous retrospective studies published in renowned international journals. Yeha Lee, CEO of VUNO said, "The significance of this research lies in its successful execution of the first multicenter prospective study with many variables and challenges, thereby reaffirming the consistent predictive performance and versatility of VUNO Med®-DeepCARS™" and he said, adding "We will continue to enhance the product's credibility in clinical settings by conducting additional prospective research. We are committed to introducing it to more medical settings as essential care to ensure patient safety." SOURCE VUNO Inc.