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Found 157 results
  1. News Article
    Talking Medicines, a social intelligence company for the pharmaceutical industry, has secured £1.1 million funding deal to scale up its AI-based platform for measuring patient sentiment. Tern, an investment company specialising in the Internet of Things (“IoT”), is the lead investor in a syndicated funding round alongside The Scottish Investment Bank, Scottish Enterprise’s investment arm. Led by CEO Jo Halliday alongside co-founders Dr Elizabeth Fairley and Dr Scott Crae, Talking Medicines will use the funds to support the launch and roll-out of a new AI data platform, which will translate what patients are saying into intelligence by providing a global patient confidence score by medicine. As part of these plans, the business intends to immediately recruit 9 new employees to the NLP data tech team. Formed in 2013 to create new ways of capturing the voice of the patient, the Glasgow-based firm uses a combination of AI, machine learning and Natural Language Processing (NLP) tech tools to capture and analyse the conversations and behaviours of patients at home, with the aim of transforming big pharma’s understanding of patient sentiment. Through mapping the patient voice from social media and connected devices to regulated medicine information, it is able to build data points to determine trends and patterns of patient sentiment across medicines. The round brings the total raised by the firm to £2.5m, including three previous seed funding rounds with previous investors including impact investor SIS Ventures and the Scottish Investment Bank. Talking Medicines CEO Halliday, said: “This investment will scale our team and the development of our AI, ML, NLP tech tools to translate what patients are saying into actionable pharma grade intelligence through our global patient confidence score by medicine.”
  2. News Article
    Virtual wards, at-home antibiotic kits and using artificial intelligence in GP surgeries are among new initiatives to be trialled as part £160m funding to tackle waiting lists in the NHS. NHS England announced the funding to aid in the health service’s recovery after the pandemic, after figures last month revealed the number of people waiting to begin hospital treatment in England had risen to a new record. A total of 4.7 million people were waiting to start treatment at the end of February - the highest figure since records began in August 2007. But NHS England said indicators suggest operations and other elective activity were at four-fifths of pre-pandemic levels in April, which is "well ahead" of the 70% threshold set out in official guidance. It said it is working to speed up the health service's recovery by trialling new ways of working in 12 areas and five specialist children's hospitals. The so-called "elective accelerators" will each get some of the £160m as well as extra support for new ways to increase the number of elective operations, NHS England said. Tens of thousands of patients in the trial areas will be part of initiatives including a high-volume cataract service, one-stop testing facilities and pop-up clinics to allow patients to be seen and discharged closer to home. Other trials over the next three months include virtual wards and home assessments, 3D eye scanners, at-home antibiotic kits, "pre-hab" for patients ahead of surgery, artificial intelligence in GP surgeries and so-called "Super Saturday" clinics, bringing multi-disciplinary teams together at the weekend to offer more specialist appointments. Read full story Source: The Independent,
  3. News Article
    New research has emerged that may be able to diagnose dementia after a single brain scan. Scientists have begun testing a new artificial intelligence system that could identify the condition and predict predict whether it will remain stable for many years, slowly deteriorate or need immediate treatment. Prof Zoe Kourtzi, of Cambridge University and a fellow of national centre for AI and data science The Alan Turing Institute, said "If we intervene early, the treatments can kick in early and slow down the progression of the disease and at the same time avoid more damage". Read full story. Source: BBC News, 10 August 2021
  4. News Article
    Artificial intelligence (AI) tools and deep learning models are a powerful tool in cancer treatment. They can be used to analyse digital images of tumour biopsy samples, helping doctors quickly classify the type of cancer, predict prognosis and guide a course of treatment for the patient. However, unless these algorithms are properly calibrated, they can sometimes make inaccurate or biased predictions. A new study led by researchers from the University of Chicago shows that deep learning models trained on large sets of cancer genetic and tissue histology data can easily identify the institution that submitted the images. The models, which use machine learning methods to "teach" themselves how to recognise certain cancer signatures, end up using the submitting site as a shortcut to predicting outcomes for the patient, lumping them together with other patients from the same location instead of relying on the biology of individual patients. This in turn may lead to bias and missed opportunities for treatment in patients from racial or ethnic minority groups who may be more likely to be represented in certain medical centres and already struggle with access to care. "We identified a glaring hole in the in the current methodology for deep learning model development which makes certain regions and patient populations more susceptible to be included in inaccurate algorithmic predictions," said Alexander Pearson, one of the authors of the study. Read full story Source: Digital Health News, 22 July 2021
  5. News Article
    Google has unveiled a tool that uses artificial intelligence to help spot skin, hair and nail conditions, based on images uploaded by patients. A trial of the "dermatology assist tool", unveiled at the tech giant's annual developer conference, Google IO, should launch later this year, it said. The app has been awarded a CE mark for use as a medical tool in Europe. A cancer expert said AI advances could enable doctors to provide more tailored treatment to patients. The AI can recognise 288 skin conditions but is not designed to be a substitute for medical diagnosis and treatment, the firm said. Read full story Source: BBC News, 18 May 2021
  6. Event
    This webinar chaired by Dr Jennifer Dixon, Chief Executive of The Health Foundation and featuring Dr Tim Ferris, NHS England’s Director of Transformation, will explore the next steps for service transformation at scale. Against the backdrop of the recent Wade-Gery review, the data strategy, the forthcoming Goldacre review and AI strategy, the new tech fund to support elective recovery, and a renewed focus on delivering the tech ambitions outlined in the Long Term Plan, how can these be linked to support service transformation better in practice? What will be different this time? Register
  7. Event
    This Westminster Health Forum conference will examine the priorities and next steps for utilising AI-driven technologies within health and social care. Delegates will consider the opportunities for increased use, what is needed to tackle barriers to implementation, data protection, questions of ethics and bias, wider regulatory challenges, and priorities for research. It will be a timely opportunity to consider next steps for harnessing AI-based healthcare solutions to deliver streamlined and effective care following developments made during the pandemic - and in the context of the development of an AI Strategy for Health and Social Care. Overall, the agenda will bring out latest thinking on: priorities for the development of a national AI Strategy for Health and Social Care addressing the key ethical and legal issues in the development of AI-based health solutions key issues surrounding data security and sharing, priorities for ensuring patient anonymity, data confidentiality and providing transparency around data use the future for research and innovation in the development of AI-driven technologies priorities for workforce education and training around AI health solutions addressing barriers to the use of AI in healthcare, developing digital infrastructure across the health service, and improving the diversity of clinical research data. Register
  8. Event
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    AI mainly refers to doctors and hospitals analysing vast data sets of potentially life-saving information through AI algorithms. However, in primary care it has been getting an increasingly important role in standardising triaging, creating intelligent patient pathways and supporting prioritisation and decision making with urgency indications and differential diagnoses. In this webinar, we will provide an overview of applications of AI in improving patient flow and patient transfer within healthcare settings. Learn how organisations are achieving real results with AI supported triaging. Discover how to leverage Intelligent patient pathway management can increase capacity. See how you can build a strong data-driven organisation, while improving staff morale and the patient experience. Register
  9. Content Article
    An increasing number of healthcare artificial intelligence (AI) applications are in development or already in use, but the safety impact of using AI in healthcare is largely unknown. This qualitative study in the journal Safety Science aimed to explore how different stakeholders (patients, hospital staff, technology developers and regulators) think about safety and the safety assurance of healthcare AI. Through a series of interviews, the authors assessed stakeholder perceptions of an AI-based infusion pump in the intensive care unit. Participants expressed perceptions about: the potential impact of healthcare AI requirements for human-AI interaction safety assurance practices and regulatory frameworks for AI and the gaps that exist how incidents involving AI should be managed. The authors concluded that there is currently a technology-centric focus on AI safety, and a wider systems approach is needed. They also identified a need for greater awareness of existing standards and best practice among technology developers.
  10. Content Article
    The Indian Liver Patient Dataset (ILPD) is used extensively to create algorithms that predict liver disease. Given the existing research describing demographic inequities in liver disease diagnosis and management, these algorithms require scrutiny for potential biases. Isabel Straw and Honghan Wu address this overlooked issue by investigating ILPD models for sex bias. They demonstrated a sex disparity that exists in published ILPD classifiers. In practice, the higher false negative rate for females would manifest as increased rates of missed diagnosis for female patients and a consequent lack of appropriate care. Our study demonstrates that evaluating biases in the initial stages of machine learning can provide insights into inequalities in current clinical practice, reveal pathophysiological differences between the male and females, and can mitigate the digitisation of inequalities into algorithmic systems. An awareness of the potential biases of these systems is essential in preventing the digital exacerbation of healthcare inequalities.
  11. Content Article
    This is part of our series of Patient Safety Spotlight interviews, where we talk to people working for patient safety about their role and what motivates them. Clive talks to us about the important role of digital technologies in tackling the big issues healthcare faces, the need for digital tools and records to be joined-up and interoperable, and how his experiences as a carer have shaped how he sees patient safety.
  12. Content Article
    This is part of our series of Patient Safety Spotlight interviews, where we talk to people working for patient safety about their role and what motivates them. Mark talks to us about how he came to work in healthcare, the vital role of safety scientists and human factors specialists in improving patient safety, and the challenges involved in integrating new technologies into the health system.
  13. Content Article
    A digital transformation is underway in healthcare and health technology. But what exactly do the smart hospitals of the future look like? Are we heading for a fully virtual health experience? Whether it’s AI and machine learning, or another form of innovation – it’s clear to see that health tech, and healthcare, is changing drastically. The words “smart hospital” and “virtual hospital wards” have eased their way into our vocabulary – and they will soon be the driving force of healthcare everywhere. So what would smart hospitals look like? And what should we be expecting between now and 2050? Health Tech World asked some of the leading experts in the field to give us their predictions as well as their expertise on what the healthcare of the next few decades will look like.
  14. Content Article
    This report by the consultancy firm Deloitte looks at patient safety across biopharmaceutical (biopharma) value chains, arguing that change is needed to make medications safer for patients and add value to pharmaceutical products. The authors highlight that there is currently great potential for strategies to increase safety, improve equity and enhance patient engagement and experience. Advances in artificial intelligence (AI) technologies and data analytics, combined with increased incidence of adverse event reports (AERs) and increasing expectation of more personalised, preventative, predictive and participatory (4P) medicine, present an opportunity to improve pharmacovigilance.
  15. Content Article
    This research is a collaboration between the NHS AI Lab and Health Education England. Its primary aim is to inform the development of education and training to develop healthcare workers’ confidence in artificial intelligence (AI).
  16. Content Article
    This report explores the factors influencing healthcare workers’ confidence in AI-driven technologies. A second report will detail how their confidence can be developed through education and training.
  17. Content Article
    This open access book addresses the future of work and industry by 2040—a core interest for many disciplines inspiring a strong momentum for employment and training within the industrial world. The future of industrial safety in terms of technological risk-management, although of obvious concern to international actors in various industries, has been quite sparsely addressed. This brief reflects the viewpoints of experts who come from different academic disciplines and various sectors such as oil and gas, energy, transportation, and the digital and even the military worlds, as expressed in debates and discussions during a two-day international seminar. 'Managing future challenges for safety' will interest and influence researchers considering the future effects of a number of currently developing technologies and their practitioner counterparts working in industry and regulation.
  18. Event
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    NCRI Virtual Showcase will feature a number of topical sessions, panel discussions and proffered paper presentations covering the latest discoveries across: Big data and AI Prevention and early detection Immunology and immunotherapy Living with and beyond cancer Cancer research and COVID-19 Further information and registration
  19. Content Article
    As trusts consider clearing the waiting list, there is an absence of objective approaches to prioritisation. There are 40 million variations of operative type and the NHS elective waiting list may reach more than 10 million. A coronavirus second wave may cause further delays and expansion of the waiting list. This blog from hub topic lead Richard Jones describes a proven approach to prioritising the waiting list built around individualised risk-adjustment for each patient and evolved from the core POSSUM methodology that is widely used for individual risk assessment pre-operatively.
  20. Content Article
    The COVID-19 crisis has created a watershed moment for the NHS, demanding a reappraisal of how essential services are delivered to the public. Even prior to COVID-19, the NHS recognised a pressing need to rethink healthcare using user-centred design principles, based on populations, not organisations. With the advent of the pandemic that pressing need has become an operational imperative. Digital capability has been and will continue to be a key part of transformation, but will only work when aligned with reforms in other key enablers such as financial flow, workforce planning and regulation. Many industries have already made the shift to enabling collaboration and innovation through more agile models of delivery by embracing technologies like artificial intelligence (AI), internet of things (IoT) and/or flexible and secure forms of (multi) cloud storage. Health, on the other hand, until now has introduced new technologies with the objective of improving existing pathways and service delivery models. There is now an opportunity to reimagine healthcare, driving true transformation enabled by digital capabilities.
  21. Content Article
    The use of artificial intelligence in healthcare is often touted as a technology which can transform how tasks are carried out across the NHS. Rachel Dunscombe, CEO of the NHS digital academy and director for Tektology, and Jane Rendall, UK managing director for Sectra, examine what needs to happen to make sure AI is used safely in healthcare in this article for Digital Health.
  22. Content Article
    Although millions of patients with cancer around the world face delays in diagnosis and treatment because of the diversion of resources during the COVID-19 pandemic, there is a growing expectation that telemedicine may play a central role in easing the backlog. This Lancet Digital Health article explores how telemedicine will be key as healthcare systems move forward in tackling the backlog in not only cancer treatment but also diagnosis, and how augmented intelligence (AI) could be used to help to optimise its use.
  23. Content Article
    The Royal Society of Medicine (RSM) has exclusive interviews from leading figures in healthcare on their website, these podcasts focus on a variety of topics within medicine and healthcare, covering everything from mental health and paediatric care to the medical workforce crisis and patient safety.  In this episode, Kaji Sritharan talks to Dr Dominic King, Health Lead of DeepMind about the role of Artificial Intelligence and the development and introduction of Digital Technologies into the NHS.
  24. Content Article
    Healthcare is advancing at a quicker rate than ever before. With the introduction of Artificial Intelligence (AI), you can now get a cancerous mole diagnosed with a mobile device. The reliance on technology has never so great. With technology predicted to replace as much as 80 per cent of a physician’s everyday routine, we must question what the new threats posed to patient safety are? This article, written by CFC Underwriting, explains some of the pitfalls of the new technology. CFC is a specialist insurance provider.
  25. Content Article
    The use of artificial intelligence (AI) in patient care currently is one of the most exciting and controversial topics. It is set to become one of the fastest growing industries, and politicians are putting their weight behind this, as much to improve patient care as to exploit new economic opportunities. In 2018, the then UK Prime Minister pledged that the UK would become one of the global leaders in the development of AI in healthcare and its widespread use in the NHS. The Secretary for Health and Social Care, Matt Hancock, is a self-professed patient registered with Babylon Health’s GP at Hand system, which offers an AI-driven symptom checker coupled with online general practice (GP) consultations replacing visits at regular GP clinics.
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