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Mashup Score: 20Forecasting Artificial Intelligence Trends in Health Care: Systematic International Patent Analysis - 3 month(s) ago
Background: Artificial intelligence (AI)– and machine learning (ML)–based medical devices and algorithms are rapidly changing the medical field. To provide an insight into the trends in AI and ML in health care, we conducted an international patent analysis. Objective: It is pivotal to obtain a clear overview on upcoming AI and MLtrends in health care to provide regulators with a better position to foresee what technologies they will have to create regulations for, which are not yet available on the market. Therefore, in this study, we provide insights and forecasts into the trends in AI and ML in health care by conducting an international patent analysis. Methods: A systematic patent analysis, focusing on AI- and ML-based patents in health care, was performed using the Espacenet database (from January 2012 until July 2022). This database includes patents from the China National Intellectual Property Administration, European Patent Office, Japan Patent Office, Korean Intellectual Prope
Source: ai.jmir.orgCategories: General Medicine News, General HCPsTweet
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Mashup Score: 9Exploring Machine Learning Applications in Pediatric Asthma Management: Scoping Review - 4 month(s) ago
Background: The integration of machine learning (ML) in predicting asthma-related outcomes in children presents a novel approach in pediatric health care. Objective: This scoping review aims to analyze studies published since 2019, focusing on ML algorithms, their applications, and predictive performances. Methods: We searched Ovid MEDLINE ALL and Embase on Ovid, the Cochrane Library (Wiley), CINAHL (EBSCO), and Web of Science (core collection). The search covered the period from January 1, 2019, to July 18, 2023. Studies applying ML models in predicting asthma-related outcomes in children aged <18 years were included. Covidence was used for citation management, and the risk of bias was assessed using the Prediction Model Risk of Bias Assessment Tool. Results: From 1231 initial articles, 15 met our inclusion criteria. The sample size ranged from 74 to 87,413 patients. Most studies used multiple ML techniques, with logistic regression (n=7, 47%) and random forests (n=6, 40%) being the m
Source: ai.jmir.orgCategories: General Medicine News, Allergy-ImmunologyTweet-
This review highlights the diverse application of Machine Learning in predicting pediatric #asthma outcomes, with each model offering unique strengths and challenges. https://t.co/77L36Q88AE https://t.co/tJrptki6Jw
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Mashup Score: 13
Background: Diabetes mellitus is the most challenging and fastest-growing global public health concern. Approximately 10.5% of the global adult population is affected by diabetes, and almost half of them are undiagnosed. The growing at-risk population exacerbates the shortage of health resources, with an estimated 10.6% and 6.2% of adults worldwide having impaired glucose tolerance and impaired fasting glycemia, respectively. All current diabetes screening methods are invasive and opportunistic and must be conducted in a hospital or laboratory by trained professionals. At-risk participants might remain undetected for years and miss the precious time window for early intervention to prevent or delay the onset of diabetes and its complications. Objective: We aimed to develop an artificial intelligence solution to recognize elevated blood glucose levels (≥7.8 mmol/L) noninvasively and evaluate diabetic risk based on repeated measurements. Methods: This study was conducted at KK Women’s an
Source: ai.jmir.orgCategories: General Medicine News, General HCPsTweet-
A few months ago a company called Actxa reached out to me claiming that they are the first in the world to have blood glucose monitoring technology for wearables using #AI. I asked them to prove their claims with a peer-reviewed paper and now they did. https://t.co/ewrwSDt9Wr
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By analyzing patents, we've been able to forecast the key areas of healthcare and medicine that will be revolutionized in the coming years, as well as those that will require more robust guidelines and to ensure the safe and ethical integration of AI. https://t.co/irFC9Te75d