Temasek-backed disease outbreak intelligence AI set for 2026 pilots
Temasek-backed disease outbreak intelligence AI set for 2026 pilots | Healthcare IT News
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Tag: disease
CIO Podcast – Episode 104: Leveraging AI with Madhu Narasimhan
For the 104th episode of the CIO podcast hosted by Healthcare IT Today, we are joined by Madhu Narasimhan, CIO at DaVita, to talk about leveraging AI! We kick this episode off by discussing…
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The role of digital twins in P4 medicine: A paradigm for modern healthcare
P4 medicine (Predictive, Preventive, Personalized, and Participatory) offers a comprehensive approach to personalized healthcare, emphasizing both the transition from disease to wellness and the importance of preventive care. In this perspective, we propose a…
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A multi-criterion feature integration framework for accurate diagnosis of Sjögren’s disease using routine laboratory tests
Sjögren’s disease (SjD) is a common systemic autoimmune disease that remains difficult to diagnose early due to non-specific symptoms and lack of definitive biomarkers. This multicentre retrospective cohort study analysed data from 34,958 patients…
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The case for scaling AI in screening for disease
Professor Alicja Rudnicka, professor of health and medical sciences at City St George’s, University of London (Credit: Alicja Rudnicka)
We must understand what responsible AI adoption requires when moved out of controlled trials and…
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AI testing platform removes commercial bias for NHS use
Professor Alicja Rudnicka from the School of Health and Medical Sciences at City St Georges, University of London (Credit: Professor Alicja Rudnicka, City St George’s, University of London)
Researchers have developed a testing platform…
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Fair positive unlabeled learning for predicting undiagnosed Alzheimer’s disease in diverse electronic health records
Alzheimer’s Disease (AD), the most common neurodegenerative disease, is underdiagnosed and more prominent in underrepresented groups. We performed semi-supervised positive unlabeled learning (SSPUL) coupled with racial bias mitigation for equitable prediction of undiagnosed AD…
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A systematic review of explainable artificial intelligence methods for speech-based cognitive decline detection
Artificial intelligence models analyzing speech show remarkable promise for identifying cognitive decline, achieving performance comparable to clinical assessments. However, their “black box” nature poses significant barriers to clinical adoption, as healthcare professionals require transparent…
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Trends and effectiveness of digital health management in postdischarge coronary artery disease across COVID19 pandemic
The effectiveness of digital health management (DM) in post-discharge care for patients with coronary artery disease (CAD) remains insufficiently explored, particularly across public health emergencies. A total of 24,129 patients with CAD enrolled in…
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Information content as a health system screening tool for rare diseases
Rare diseases (RD) affect 3.5–5.9% of the global population, yet patients often endure a diagnostic odyssey averaging around 5–6 years, navigating multiple specialties and referrals. This study investigates the use of information content (IC)…
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