AI can detect warning signs of heart attack, scientists say
Developed by University of Dundee researchers, the AI analyses digital retinal photographs to provide personalised risk predictions in under a second.
The technology was trialled on eye scans of individuals with type 2 diabetes and achieved 70 per cent accuracy in predicting major cardiovascular events.
Experts suggest this simple, quick test could complement existing checks like blood pressure and cholesterol, allowing for earlier intervention.
While promising, further research is needed to confirm its robustness and feasibility for widespread clinical use in preventing cardiovascular diseases, the British Heart Foundation says.
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Geeky Gadgets
8 minutes ago
- Geeky Gadgets
Why Most AI Apps Fail Before Launch and How to Beat the Odds
Have you ever wondered why so many promising AI applications never make it past the prototype stage or fail to deliver on their potential? Despite the buzz around artificial intelligence, shipping a functional, scalable AI app is far from straightforward. Unlike traditional software, AI applications come with a unique set of challenges: skyrocketing operational costs, safeguarding against misuse, and the constant pressure to meet ever-evolving user expectations. It's a high-stakes balancing act where even small missteps can lead to spiraling expenses or a poor user experience. For developers and businesses alike, the road to deploying AI isn't just bumpy—it's a minefield. App developer Chris Raroque explains the hidden complexities of bringing AI-powered applications to life and uncover strategies to navigate them effectively. From optimizing operational expenses to designing user-centric platforms, you'll gain insights into the real-world challenges that go beyond the hype. Whether it's using multiple AI models to balance performance and cost or carving out a competitive edge with niche-specific solutions, this guide will show you how to overcome the hurdles that make shipping AI apps so hard. Because in a world where innovation often outpaces practicality, success lies in mastering the details that others overlook. AI App Development Challenges Cost Management: Optimizing Operational Expenses AI applications, particularly those powered by large language models, demand significant computational resources, which can lead to high operational costs. For instance, processing lengthy conversation histories or prompts for every interaction can quickly inflate expenses. To manage these costs effectively, consider adopting the following strategies: Shorten prompts to include only the most relevant information, reducing unnecessary data processing. Implement a 'window' technique to limit the conversation history processed by the model, focusing only on recent and pertinent interactions. These methods help minimize resource consumption while maintaining a seamless user experience. By optimizing operational expenses, you can ensure your application remains cost-effective without compromising its functionality or quality. Abuse Prevention: Protecting Your System AI systems are inherently vulnerable to misuse, which can result in excessive costs, degraded performance, or even system failures. To safeguard your application and maintain its reliability, you should implement robust protective measures, such as: Setting limits on message size and user activity, such as daily or monthly usage caps, to prevent overuse. Incorporating a remote kill switch to disable abusive accounts in real time, making sure immediate action against misuse. Using analytics tools to monitor usage patterns and detect anomalies that may indicate abuse. These safeguards not only protect your system from potential threats but also ensure a consistent and reliable experience for all users, fostering trust and satisfaction. The Real Challenges of Deploying AI Apps Watch this video on YouTube. Browse through more resources below from our in-depth content covering more areas on AI application development. Using Multiple AI Models: Balancing Efficiency and Performance Relying on a single AI model for all tasks may seem straightforward, but it is often inefficient and costly. Instead, deploying multiple models optimized for specific tasks can significantly enhance both performance and cost efficiency. For example: A lightweight model can handle basic queries quickly and efficiently. A more advanced model can address complex or nuanced requests that require deeper analysis. By incorporating a decision layer, your system can dynamically select the most appropriate model based on the user's input. This approach ensures that resources are allocated efficiently, reducing costs while maintaining high levels of performance and responsiveness. Platform Optimization: Designing for the Right Environment The success of your AI application depends heavily on how well it aligns with its intended platform. For example, if your application is primarily used on mobile devices, adopting a mobile-first design approach is essential. Features such as voice dictation, quick commands, and streamlined interfaces can significantly enhance usability for on-the-go users. By tailoring your design to the platform, you can create a seamless and intuitive user experience that meets the specific needs of your audience. Framework Utilization: Accelerating Development Building an AI application from scratch can be a time-intensive and error-prone process. To streamline development and improve reliability, you can use existing frameworks like the Versel AI SDK or similar tools. These frameworks offer pre-built functionalities that simplify the development process, including: Streaming capabilities for real-time interactions, enhancing responsiveness. Error handling mechanisms to improve system stability and reliability. Tool integration options to expand the functionality of your application. By using proven frameworks, you can focus on developing core features while reducing development time and making sure a stable, high-quality product. Personalization: Delivering Tailored User Experiences Personalization plays a crucial role in creating engaging and user-friendly AI applications. Allowing users to specify preferences in natural language can significantly enhance their experience. For instance, users might request a specific tone, style, or level of detail in responses, and your application can adapt accordingly. 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Key Considerations for Successful AI Application Development To navigate the complexities of AI application development effectively, keep the following considerations in mind: Monitor costs and usage from the outset to avoid unexpected expenses and ensure long-term sustainability. Use multiple models to balance efficiency and performance, optimizing resource allocation. Design with the intended platform in mind to create a seamless and intuitive user experience. Use existing frameworks to accelerate development and enhance system reliability. Focus on niche-specific solutions to differentiate your product and meet the unique needs of your target audience. By addressing these factors with careful planning and strategic execution, you can create AI applications that are not only functional but also scalable, cost-effective, and user-friendly. In an increasingly competitive landscape, these considerations will help ensure the success and longevity of your AI product. Media Credit: Chris Raroque Filed Under: AI, Guides Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
Daily Mail
9 minutes ago
- Daily Mail
Kiss of life: Mother was saved from dying from sepsis during childbirth after partner noticed something wrong when they locked lips
A mother was saved from dying from sepsis during childbirth after her partner noticed that something was wrong when they locked lips. Kerri-Louise Gilchrist gave birth to her daughter Layla, now 11 months, on August 3 last year, under terrifying and life-threatening circumstances. The 33-year-old was induced after her boyfriend, Hugh Marshall, 35, noticed her cold temperature and blue lips while kissing her. Sensing that something was gravely wrong, he immediately alerted doctors to the signs of sepsis and Ms Gilchrist was given an IV drip of antibiotics. Layla was cut out through an episiotomy and eventually delivered successfully with a ventouse. But in the process, Ms Gilchrist lost 2885ml, more than five pints, of blood. Having sat with her feet in stilts for three hours as she waited doctors to remove her placenta, she ultimately required two blood transfusions to save her life. Ms Gilchrist, a carer from Great Malvern, Worcestershire, said that her partner instinctively 'knew there was something wrong' after the pair locked lips. The mother-of-two, who described having 'such an easy' birth with her eight-year-old son Teddy, said that Mr Marshall had not given her a 'proper kiss', but instead a deliberately disguised 'temperature check'. Ms Gilchrist, a carer from Great Malvern, Worcestershire, said that her partner Hugh Marshall (both pictured) instinctively 'knew there was something wrong' after the pair locked lips. The mother-of-two said that Mr Marshall had given her a kiss as a disguised 'temperature check' Recalling the terrifying ordeal, she said: 'The nurses didn't notice anything until my partner said to them, you're not actually looking at your patient, her palms and lips are blue - that's a sign of sepsis. 'I'd been like that for a couple of hours at that point. Within two minutes of him saying that, I had 11 people in the room. 'You have somebody that's going to stand your ground for you. I was in no fit state to argue for myself, I couldn't care for myself. I wouldn't be here if it wasn't for Hugh.' Sepsis, a life-threatening condition caused by the body's extreme response to infection, results in up to 48,000 deaths in the UK each year, according to the UK Sepsis Trust. A leading cause of death in the UK, its main symptoms include a fever, rapid heart rate and breathing, feelings of confusion and difficulty breathing. Ms Gilchrist said she first noticed her waters breaking on July 28, 2024 when she was only 36 weeks and five days into pregnancy. But despite ringing Worcestershire Royal Hospital with her concerns, she was told twice over three days that she'd 'probably just weed'. After calling the hospital for a third time on August 1, having began to experience reduced mobility, she was eventually admitted. Ms Gilchrist said: 'They did the swab, came back and said, your waters are going. I'd been telling them that since Monday. 'I was induced at 7am on Friday August 2 morning for what ended up being a 36-hour labour until 11pm on Saturday night. 'I was pumped with all sorts because I couldn't stand the pain, so I had an epidural. I'd give birth to my son again every day, it was so easy, but with Layla it was so, so painful.' Adding that medical professionals 'didn't pay any attention to me' and that she only survived due to her partner, a technology professional, noticing the signs, Ms Gilchrist recalled: 'They started the IV drip of antibiotics at 8pm on Friday. 'My daughter was still inside me and they said they wouldn't give me a caesarean because there was somebody else waiting. 'The IV really hurt and I said that to them, it really hurts, it shouldn't hurt. They didn't pay any attention to me. The state of my arm, the vein exploded and caused a blood clot, and it caused tendon damage to two fingers.' Ms Gilchrist was eventually given an episiotomy when Layla started to go into stress. She said: 'After they pulled Layla out, they left me in the stilts for three hours because they hadn't got my placenta. They left me bleeding out. 'They weren't measuring the blood I was losing and told me it was normal.' Describing her partner as 'the sweetest man ever', Ms Gilchrist said that the doctors eventually realised that 'they were killing me', Having lost five pints of blood and requiring two blood transfusions, she then spent four nights in hospital recovering. Later suffering with arm pain due to the blood clot damage, she was unable to hold her daughter 'for a couple of months' and also could not breastfeed due to the trauma blocking her milk supply. Adding that an anesthetist said Ms Gilchrist had been 'pounding on heaven's door', the mother-of-two said medical professionals were 'surprised I'm alive'. She added: 'Doctors put it down as a pre-terminal event, which is the stage before death. 'I'm a stubborn bugger. At some point in there they said, how are you awake? Let alone talking to us right now. I said, I will shut my eyes when I know that I'm going to live. Until that point, I'm not going to shut my eyes. 'There was a point where I don't know if I died, but through the door I saw my mum who'd passed in April 2024. Staying awake was sheer willpower. Whenever I closed my eyes I saw my eight-year-old son, Teddy, and I'd force myself to open my eyes.' What are the key symptoms of sepsis? Sepsis, known as the 'silent killer', strikes when an infection such as blood poisoning sparks a violent immune response in which the body attacks its own organs. In the UK, it affects 245,000 people each year, with 48,000 sepsis-related deaths, according to the UK Sepsis Trust. If caught early enough, it's easily treated with intravenous antibiotics and fluids, but these must be given as soon as sepsis is suspected - it strikes with frightening speed and, for every hour of delay, a patient's chance of dying increases 8 per cent. The six signs of something potentially deadly can be identified by the acronym 'SEPSIS': Slurred speech or confusion. Extreme shivering or muscle pain. Passing no urine in a day. Severe breathlessness. Skin that's mottled or discoloured. Source: NHS UK. Lalya, who spent two additional days in hospital with an IV drip in case the sepsis had passed to her, is now doing 'really well', with Ms Gilchrist describing her as 'totally brilliant' and 'so funny'. But she said that her life-threatening ordeal served as a terrifying reminder that birth can often come with its challenges, adding that 'sometimes it's life or death'. Issuing a stark warning for others to 'trust your gut', Ms Gilchrist added: 'I know my body and I knew something was wrong.' 'Layla's fine, she's good - the one blessing in this. She had to stay in hospital for two days with an IV drip just in case sepsis had passed to her. But she's great. Developmentally, she's doing well. She's totally brilliant, so funny. Justine Jeffery, Director of Midwifery for Worcestershire Acute Hospitals NHS Trust, said the trust were 'sorry if Ms Gilchrist is unhappy with the care she received from us.' She added: 'We are committed to providing the highest quality care for all the families we look after. 'Ms Gilchrist was closely monitored by our team. It became clear that she would need to have her placenta safely removed under anaesthetic and in sterile conditions and she was transferred to an operating theatre as soon as one was available. 'Her blood loss was also closely monitored and she received a blood transfusion while in theatre and another one subsequently. She remained well and stable following this and was subsequently transferred to our postnatal ward before going home the following day. 'One of our senior midwives talked to Ms Gilchrist about the concerns she had around aspects of her care following the birth of her baby, and we would welcome the opportunity to meet with her again if there are any new or unresolved issues she wants to talk through with us.'
BBC News
9 minutes ago
- BBC News
Derby and Burton hospitals wants maternity restrictions removed
The trust in charge of Derby and Burton hospitals has asked the health watchdog to remove restrictions put on its maternity services after they were rated Care Quality Commission (CQC) served University Hospitals of Derby and Burton NHS Trust (UHDB) with eight Section 31 notices following inspections at the Royal Derby Hospital and Queen's Hospital Burton in 2023 and a further five in said the CQC had now removed six of the eight restrictions it received in 2023 and the trust had made applications to remove the shows the mortality rate for newborns at both hospitals has been below the NHS average for more than 12 months. 'Working at pace' In 2023 the CQC identified major failings in maternity services at both hospitals and ordered the trust to urgently update training, improve cleanliness and ensure safe levels of commission utilised Section 31 of the Health and Social Care Act 2008, which gives it the powers to urgently alter or remove conditions of then the trust said it had been "working hard" to improve the quality of care and experience for women and babies through a dedicated improvement programmeIt said compliance against Saving Babies Lives, an evidence-based national maternity safety ambition had improved from 33% in September 2023 to 86% in June Noble, UHDB's director of midwifery, said: "While we know from our own safety data and from our engagement with women and families that we have made improvements, we are not complacent and are absolutely committed to continuing this work at pace." UHDB said the Section 31 restrictions from 2023 which had now been removed by the CQC were for effective system of fetal monitoring, fetal monitoring training and compliance, fresh eyes implementation, clinical skills training compliance, rates of haemorrhage and appropriate senior remaining two conditions from 2023 it has applied to have removed are assessment and management haemorrhage and audit and governance of the five conditions still in place from 2024 are co-ordinated care approach to maternity, visible effective medical leadership, birth centre neonatal equipment accessible and effective process for handovers of care and induction of labour.
