Blair (left) and Clegg hosted the private dinner at the five-star Corinthia hotel in London in January. Blair (left) and Clegg hosted the private dinner at the five-star Corinthia hotel in London in January. Exclusive: Six tech leaders dined with investment minister, documents reveal, underlining growing influence of ex-PM's consultancy Tony Blair and Nick Clegg hosted a private dinner earlier this year at which a select group of technology entrepreneurs were given access to a key minister, official documents have revealed. He and Clegg, the former deputy prime minister who at the time was a senior executive at Meta, invited leaders of six tech companies to dine with Poppy Gustafsson, who was the government's investment minister responsible for persuading firms to invest in Britain. Blair is an evangelical proponent of the revolutionary potential of technology to transform faltering public services and has long courted alliances with leaders in the industry.

Britons are concerned about AI's impact on the economy and jobs in particular. Britons are concerned about AI's impact on the economy and jobs in particular. TBI says poll data threatens Keir Starmer's ambition for UK to become artificial intelligence'superpower' The Tony Blair Institute warned that the poll findings threatened Keir Starmer's ambition for the UK to become an AI "superpower" and urged the government to convince the public of the technology's benefits. TBI commissioned a survey that found 38% of Britons see AI as an economic risk while 20% see it as an opportunity. The poll of more than 3,700 adults also showed that lack of trust was the biggest barrier to adoption.

In little more than 1,600 words voicing his scepticism over net zero policies, Tony Blair this week propelled himself and his increasingly powerful institute back into the national debate. In the past eight years, the former prime minister has built a global empire employing more than 900 people across more than 40 countries, providing policy advice to monarchs, presidents and prime ministers. But while Blair's thinktank has brought him influence in his post-Downing Street career, it has also renewed scrutiny on his political views and how they are shaped by his commercial relationships. The Labour MP James Frith said on Wednesday: "I give congratulations to the marketing department at the Tony Blair Institute (TBI), who have managed to time it brilliantly to get maximum coverage." Patrick Galey, the head of fossil fuel investigations at the nongovernmental organisation Global Witness, said: "Blair's well-documented links to petrostates and oil and gas companies ought to alone be enough to disqualify this man as an independent and reliable arbiter of what's possible or commonsense in the energy transition."

To enforce a strict licensing model, the UK would also need to restrict access to models that have been trained on such content, which could include US-owned AI systems. With the Trump administration signalling it will not pursue strict AI regulations and China pursuing AI growth at "breakneck speed", the UK could weaken its economic and national security interests by lagging in the AI race, said TBI. "If the UK imposes laws that are too strict, it risks falling behind in the AI-driven economy and weakening its capacity to protect national security interests," said TBI. The report said arguing that commercial AI models cannot be trained on content from the open web was close to saying knowledge workers – a broad category of professionals ranging from lawyers to researchers – cannot profit from insights they get when reading the same content. Rather than fighting to uphold outdated regulations, said TBI, rights holders and policymakers should help build a future where creativity is valued alongside AI innovation. Fernando Garibay, a record producer who has worked with artists including Lady Gaga and U2, said history has been dotted with "end-of-time claims" related to technological breakthroughs, from the printing press to music streaming.

Artificial intelligence could displace between 1m and 3m private sector jobs in the UK, though the ultimate rise in unemployment will be in the low hundreds of thousands as growth in the technology also creates new roles, according to Tony Blair's thinktank. Between 60,000 and 275,000 jobs will be displaced every year over a couple of decades at the peak of the disruption, estimates from the Tony Blair Institute (TBI) suggest. It described the figure as "relatively modest" given the average number of job losses in the UK has run at about 450,000 a year over the past decade. More than 33 million people are employed in the UK. AI, a technology that can be loosely defined as computer systems performing tasks that typically require human intelligence, has shot up the political agenda after the emergence of the ChatGPT chatbot and other breakthroughs in the field.

Traumatic brain injury (TBI) presents a significant public health challenge, often resulting in mortality or lasting disability. Predicting outcomes such as mortality and Functional Status Scale (FSS) scores can enhance treatment strategies and inform clinical decision-making. This study applies supervised machine learning (ML) methods to predict mortality and FSS scores using a real-world dataset of 300 pediatric TBI patients from the University of Colorado School of Medicine. The dataset captures clinical features, including demographics, injury mechanisms, and hospitalization outcomes. Eighteen ML models were evaluated for mortality prediction, and thirteen models were assessed for FSS score prediction. Performance was measured using accuracy, ROC AUC, F1-score, and mean squared error. Logistic regression and Extra Trees models achieved high precision in mortality prediction, while linear regression demonstrated the best FSS score prediction. Feature selection reduced 103 clinical variables to the most relevant, enhancing model efficiency and interpretability. This research highlights the role of ML models in identifying high-risk patients and supporting personalized interventions, demonstrating the potential of data-driven analytics to improve TBI care and integrate into clinical workflows.

Traumatic Brain Injury (TBI) poses a significant global public health challenge, contributing to high morbidity and mortality rates and placing a substantial economic burden on healthcare systems worldwide. The diagnosis of TBI relies on clinical information along with Computed Tomography (CT) scans. Addressing the multifaceted challenges posed by TBI has seen the development of innovative, data-driven approaches, for this complex condition. Particularly noteworthy is the prevalence of mild TBI (mTBI), which constitutes the majority of TBI cases where conventional methods often fall short. As such, we review the state-of-the-art Machine Learning (ML) techniques applied to clinical information and CT scans in TBI, with a particular focus on mTBI. We categorize ML applications based on their data sources, and there is a spectrum of ML techniques used to date. Most of these techniques have primarily focused on diagnosis, with relatively few attempts at predicting the prognosis. This review may serve as a source of inspiration for future research studies aimed at improving the diagnosis of TBI using data-driven approaches and standard diagnostic data.

The system, outlined May 14 in The Lancet: Digital Health, utilizes data from multiple institutions across Europe and was validated using scans from more than 500 patients in India. Compared with manual assessment, the CNN produced similarly accurate measurements, allowing clinicians to quantify lesion burden and progression.

Traumatic brain injury (TBI) is a common cause of disability and death in young people [1]. Caused by external impact such as blunt trauma, penetrating objects or blast waves to the head, TBI is becoming increasingly prevalent with an estimated 1.6 million individuals sustaining mild traumatic brain injury (mTBI) each year. Major causes of TBI have been vehicle related collisions, sports or combat injuries causing brain damages, including tearing injuries of white matter or hematomas resulting in nausea, disturbed sleep patterns [2], dizziness, memory and/or concentration problems, emotional disturbances and seizures. Many of whom are never hospitalized and may suffer from consequences of head injury. Lack of consensus regarding what constitutes mTBI adds to the complication of the under-diagnosis of the disease [3].

WASHINGTON – The spotlight on brain injuries suffered by American troops in Iraq in January is an example of America's episodic attention to this invisible war wound, which has affected hundreds of thousands over the past two decades but is not yet fully understood. Unlike physical wounds, such as burns or the loss of limbs, traumatic brain injuries aren't obvious and can take time to diagnose. The full impact -- physically and psychologically -- may not be evident for some time, as studies have shown links between TBI and mental health problems. They cannot be dismissed as mere "headaches" -- the word used by President Donald Trump as he said the injuries suffered by the troops in Iraq were not necessarily serious. Gen. Mark Milley, chairman of the Joint Chiefs of Staff and a veteran of combat in Iraq and Afghanistan, told reporters Thursday that the number of service members diagnosed with TBI from the Jan. 8 Iranian missile attack in Iraq has now grown beyond the 50 reported earlier this week, although he provided no specific number.