Reliable prediction of pediatric obesity can offer a valuable resource to providers, helping them engage in timely preventive interventions before the disease is established. Many efforts have been made to develop ML-based predictive models of obesity, and some studies have reported high predictive performances. However, no commonly used clinical decision support tool based on existing ML models currently exists. This study presents a novel end-to-end pipeline specifically designed for pediatric obesity prediction, which supports the entire process of data extraction, inference, and communication via an API or a user interface. While focusing only on routinely recorded data in pediatric electronic health records (EHRs), our pipeline uses a diverse expert-curated list of medical concepts to predict the 1-3 years risk of developing obesity. Furthermore, by using the Fast Healthcare Interoperability Resources (FHIR) standard in our design procedure, we specifically target facilitating low-effort integration of our pipeline with different EHR systems. In our experiments, we report the effectiveness of the predictive model as well as its alignment with the feedback from various stakeholders, including ML scientists, providers, health IT personnel, health administration representatives, and patient group representatives.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. The journey toward improved mental health by setting thoughtful and achievable goals can be a powerful strategy. Whether grappling with anxiety, depression, ADHD or other conditions, establishing personalized goals fosters a sense of direction, accomplishment and empowerment. Explore specific goals tailored to each condition, promoting overall mental well-being.

Large Language Models (LLMs), with their flexible generation abilities, can be powerful data sources in domains with few or no available corpora. However, problems like hallucinations and biases limit such applications. In this case study, we pick nutrition counselling, a domain lacking any public resource, and show that high-quality datasets can be gathered by combining LLMs, crowd-workers and nutrition experts. We first crowd-source and cluster a novel dataset of diet-related issues, then work with experts to prompt ChatGPT into producing related supportive text. Finally, we let the experts evaluate the safety of the generated text. We release HAI-coaching, the first expert-annotated nutrition counselling dataset containing ~2.4K dietary struggles from crowd workers, and ~97K related supportive texts generated by ChatGPT. Extensive analysis shows that ChatGPT while producing highly fluent and human-like text, also manifests harmful behaviours, especially in sensitive topics like mental health, making it unsuitable for unsupervised use.

It is a whole new world due to the pandemic. The life insurance industry settled more claims in the year 2021 than in 2020 due to this Black Swan event. A sudden demand for life insurance policies and increased claims induced operational changes for the insurance industry. As we head into the new financial year, there is no end yet to the anxiety as variants of the Covid-19 virus continue to emerge. Given improved economic sentiments, greater appreciation for its need and increased vaccinations, life insurance companies are expected to do a lot more in the new Financial Year (FY) 2023.

By definition, a smart city is an urban area that relies heavily on data to monitor and manage resources efficiently. The concept of smart cities assimilates information and communication technology (ICT) and internet of things (IoT) to ensure the efficacy of city operations. Smart city as a concept is gaining popularity because it promises to harness the potency of the available infrastructure and create new-age living practices to help its residents lead a better, happier life. Health is an indispensable part of smart living, and unless we improve the level of health conditions the dream of smart cities would remain incomplete. A smart city should not only aim to provide smart healthcare solutions for its citizens but foster an ecosystem that curtails the growth of disease and nurtures a healthier way of life for its citizens.

We've seen multiple use cases where smart devices like smart watches and other smart appliances have helped people maintain excellent homes and healthy bodies. Are there any smart devices or sensors that can help individuals in improving their mental health and ensure that they lead a happy life? Mental health is imperative for physical health. To live a fully healthy lifestyle, we need to take care of our mind, just as much as our body. And for that, there are some machine learning solutions and smart devices that prioritize mental well-being.

As Yuval Harari concludes in his book "Homo Deus: A Brief History of Tomorrow," mankind has managed to control famine, plague, and war in the 20th century. Now, we have new challenges to worry creative minds. The author believes that the first major project of the 21st century will be immortality, or at least the ability to cure all known diseases and extend people's lives for as long as possible. This may sound too ambitious. Technology still has a long way to go to build this futuristic picture.

Artificial intelligence (AI) is leading a technology revolution across various business verticals and sectors. Insurance is one sector which is also using artificial intelligence to change the way companies carry their businesses and provide better customer services in return. From underwriting insurance policies to offering personalized covers and improving the claim settlement process duration, AI is bringing a powerful orientation to the insurance sector at large. Here is a look at how AI can empower the insurance sector and what it may mean for you as an insurance seeker or a policyholder. Understanding The World Of AI Artificial intelligence (AI) makes good use of the huge volume of data and ensures autonomous control of machines or computers through its intelligence based software.

Next time you get your annual physical, will the internet of things play a role in that checkup? But what could that look like? IoT plays a role in a multitude of industries and verticals, we have heard how IoT will impact how John Deere helps farmers, how it impacts the way GE and Rolls-Royce manage their fleets of planes, and how ExxonMobile is using IoT to remotely monitor its facilities. The future of IoT has the potential for great influence on our personal wellbeing, but it will face some major hurdles. The IoT is imminent – and so are the security challenges it will inevitably bring. Get up to speed on IoT security basics and learn how to devise your own IoT security strategy in our new e-guide.

We've talked before about the prospects of artificial intelligence (AI) and how it will likely disrupt things like we've never seen before with some estimates predicting that up to 80% of all service jobs will be impacted. Healthcare is one area where AI is receiving a good chunk of funding. We looked before at one example of an artificial intelligence company called Enlitic that uses machine learning technology to read X-rays better than a human radiologist who makes $286,000 a year on average. There are actually quite a few artificial intelligence companies in healthcare and CB Insights recently identified 65 of them at various stages of funding. Founded just last year, Chinese company iCarbonX has taken in nearly $200 million in funding from investors that include the $200 billion Chinese internet giant Tencent.