Intensive, repeated self-report measures are an important tool for behavioral and medical researchers and practitioners who are concerned with the dynamic interplay among variables at a granular level. Many mobile health applications rely on…
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The government has acknowledged that its flagship digital reforms face significant delivery risks, citing a history of NHS IT programmes underestimating cost, complexity and timescales.
An impact statement on the NHS 10 year health plan,…
Professor Hatim Abdulhussein, chief executive at Health Innovation Kent Surrey Sussex
An initiative called TrustX has been launched to help verify, deploy, and test agentic AI for use across the NHS and social care.
It…
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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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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Background: Effective treatments for depression are available, yet many patients do not respond to treatment or experience relapse. Cognitive bias modification aims to ameliorate cognitive biases that contribute to the development and maintenance of…
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Multimodal models have enabled the integration of digital pathology, radiology, clinical information, and omics data to enhance Colorectal cancer (CRC) care. This systematic review critically appraises Multimodal digital pathology techniques applied in CRC, their…
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Delirium affects 50% of hospitalized older adults and 80% of ICU patients, yet detection rates are as low as 20–30% with traditional methods. Natural language processing (NLP) offers potential for automated detection from clinical…
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Biased and poorly documented dermatology datasets pose risks to the development of safe and generalizable artificial intelligence (AI) tools. We created a Dataset Nutrition Label (DNL) for multiple dermatology datasets to support transparent and…
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AI is transforming healthcare, yet pediatric adoption remains limited and governance is underdeveloped. We review existing frameworks and identify pediatric-specific gaps: insufficient stakeholder engagement, developmentally appropriate consent/assent, limited bias mitigation, and unclear accountability. An…
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