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'Knowing ahead of time that a patient may be at risk of harm can help us develop intervention strategies ... and adjustments to their care plan,' says Waypoint official

NEWS RELEASE WAYPOINT CENTRE ************************* It's crucial to keep patients safe when they receive care. This is especially important for mental health conditions, where early intervention can make a big difference. In recent years, the application of artificial intelligence (AI) in healthcare has shown great promise, and one area where it holds significant potential is the development of an early warning score (EWS) system for mental health patients.

Early warning scores help care teams identify early signs of a patients health getting worse so they can take action early, said Dr. Andrea Waddell, Medical Director Quality Standards and Clinical Informatics.

Knowing ahead of time that a patient may be at risk of harm can help us develop intervention strategies such as increased nursing attention and adjustments to their care plan.

Data from the Canadian Institute for Health Information in 2021-22 shows that 1 in 17 hospital stays had unintended harm, and almost half of them could have been avoided.

Waypoints Dr. Waddell is also the regional clinical co-lead for mental health and addictions at Ontario Healths Mental Health and Addictions Centre of Excellence. She and her team of researchers are seeking to change this statistic creating an EWS to prevent harm before it happens.

Artificial intelligence has revolutionized various sectors and mental health care is no exception. It can look at a lot of data, find patterns and give helpful information. When used in mental health care, AI can help detect problems early, make personalized treatment plans, and reduce the burden on healthcare providers.

While early warning scores are commonly used in acute medical settings, they havent been used as much in mental health. The EWS system involves always monitoring and analyzing each patient's specific information including historical data and AI algorithms, to understand if they might get worse. Ideally alerting care providers up to 72 hours in advance so they can help the patient sooner.

Waypoint and its expert staff care for some of the provinces most severely ill patients. The hospital has a 20-bed acute mental health program, has submitted a proposal to the Ministry of Health to add an additional 20-bed unit, and is shifting the culture intentionally to become a learning health system; making the hospital uniquely positioned to build this early warning model.

Leveraging existing frameworks, expert opinion, and literature, the hospital is proposing variables for an EWS and testing a machine-learning model on 2022 patient data. Frontline clinicians, patients, and families will provide input at every step to guide the selection of the final algorithm. Once finalized, the EWS will be piloted in some Waypoint units using a rapid-cycle quality improvement model.

Early Intervention and timely detection of deteriorating mental health conditions is really about advancing person-centred care, said Dr. Nadiya Sunderji, President and CEO. Artificial intelligence enables personalized care plans tailored to individual patients' needs, taking into account their specific risk factors, treatment history, and response patterns.

Artificial intelligence unlocks tremendous potential in developing Early Warning Score systems for mental health patients, helping healthcare professionals detect problems early. Leveraging AI's capabilities can enhance patient care, improve outcomes, and reduce the burden on mental health services. AI-driven solutions hold the key to revolutionizing mental health care for a brighter and healthier future.

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Artificial intelligence could aid treatment of mental health issues - OrilliaMatters

JPMorgan Chase & Co (NYSE: JPM) has announced a partnership with TIFIN to invest in artificial intelligence (AI) focused ventures in the financial services industry. TIFIN.AI, a new venture aimed at developing AI-based financial technology companies, will be the main focus of this collaboration. JPMorgan has expressed its commitment to exploring the potential of AI in the financial sector, with plans to leverage AI to deliver $1.0 billion of business value in 2023. The bank aims to empower professionals and individuals to make informed financial decisions by harnessing the power of AI. Earlier this year, JPMorgan was working on an AI tool similar to ChatGPT. The investment banks shares have experienced significant growth, up nearly 17% for the year. This partnership comes after JPMorgan reported strong financial results for the second quarter, driven by higher interest rates. The collaboration with TIFIN reflects JPMorgans strategy to drive value through AI and showcases their belief that AI will become an integral part of wealth and asset management interactions.

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JPMorgan Partners with TIFIN to Explore Artificial Intelligence in ... - Fagen wasanni

Imagine walking into a restaurant and being greeted by a screen that uses artificial vision to determine your dining preferences. Based on whether youre alone, with a partner, or with family, the screen offers different menu options tailored to your needs. This is just one example of how Artificial Intelligence (AI) is transforming the restaurant industry.

AI technology has been implemented in various ways to optimize processes and enhance the customer experience. For instance, AI can automate cumbersome tasks in the kitchen, such as real-time reservation management and voice command inventory tracking. This not only saves time but also reduces errors and improves efficiency.

In Spain, the digital transformation of the hospitality industry is well underway. According to a report by BCC Innovation and Delectatech, over 15% of the industry is digitized, and 32% is in the process of digitization. Madrid, Barcelona, the Balearic Islands, and Mlaga are leading the way in Spains digital revolution.

Startups like DynamEat and Satis.IA are paving the path for innovative AI solutions in the restaurant sector. DynamEat applies airline and hotel technologies to streamline pricing, allowing restaurants to dynamically adjust prices based on supply and demand. Meanwhile, Satis.IA uses AI-powered systems to prevent errors and train personnel, maintaining quality standards using artificial vision.

NotCo, a plant-based product startup, stands out by using AI algorithms to create perfect combinations of flavors and textures that mimic animal-based products. By using a list of vegetables, their AI algorithm called Giuseppe can create plant-based alternatives with similar taste and texture profiles.

AI also benefits customers by allowing for personalized taste and nutrition customization. Projects in the United States, the United Kingdom, and Japan use medical information gathered through DNA, microbiota, or blood tests to design special diets or nutritional supplements. This can be especially useful for individuals with allergies, intolerances, and dietary restrictions.

While the implementation of AI in the restaurant industry has brought forth benefits, it has also sparked debates about privacy. Nonetheless, experts argue that AI technologies are not invasive and that personalized attention is still highly valued by customers.

As the restaurant industry embraces AI, we can expect to see more smart restaurants like AINA Smart Restaurant in Barcelona, which uses tablets for ordering and entertainment purposes. Robots with AI capabilities are also being introduced, such as those seen in the Urban Poke chains Pokesito, which can deliver orders to tables and interact with customers.

The era of AI in the restaurant industry has arrived, transforming operations and elevating customer experiences.

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How Artificial Intelligence is Transforming the Restaurant Industry - Fagen wasanni

Artificial intelligence (AI) is becoming increasingly advanced and prevalent in todays society. However, along with its many benefits, there are also potential issues that arise. One artist from Lansing, Michigan, recently fell victim to the misuse of AI technology when someone used it to create and send a non-consensual nude photo of her.

Mila Lynn, a local painter, discovered that someone online had used AI to transform a fully clothed picture of her into a nude image. Shocked by this violation of her privacy, she expressed her disbelief at being the inspiration for someone elses digital art.

Lynn explained that she had received a message from a stranger on Facebook regarding a mural painting inquiry. However, the conversation quickly took an inappropriate turn, with the person asking if she did modeling work. Lynn adamantly declined, stating that it was not something she engaged in. It was then that the person revealed they had found photos of her online.

Soon after, Lynn received the non-consensual nude photo generated by AI, which had been created using her original fully clothed picture. She expressed her frustration at not knowing what to do since she had not intentionally shared any inappropriate images.

Instances like these, where AI technology is used to exploit individuals, are unfortunately not uncommon. Experts in the AI field acknowledge the need to regulate the proper usage of this technology. One proposed solution is the implementation of watermarks or other identifying features on AI-generated images or videos to help detect authenticity.

Although Lynn is unsure who is responsible for creating the AI-generated image of her, she chose to speak out about her experience to raise awareness of the potential misuse of AI. She encouraged others who find themselves in similar situations to report it, regardless of how embarrassing it may be.

This incident serves as a reminder of the importance of vigilance and caution in the digital age. As AI continues to develop, it is crucial to find ways to protect individuals from the misuse of this powerful technology.

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Artificial Intelligence Used to Create Non-consensual Nude Photos - Fagen wasanni

Nuclear science, towering 200m power plants, and millions of miles of electrical cable are some of the things making the power industry one of the most process driven on Earth. Power companies at every stage of the value chain must make decisions regarding how to best use and maintain their assets to balance supply with demand. They are therefore natural candidates for the integration of AI, which has the potential to enhance generation, transmission, distribution, and the experience for end users.

The power industry is often considered as being stuck in its ways. Not out of stubbornness, but due to the difficulty in digitally transforming age-old infrastructure and training an ageing workforce. The question is therefore how can power companies integrate AI into their business models?

AI implementation in the power industry starts with equipment. Most power plants and electricity grids typically have lifespans extending decades. Therefore, while new AI-powered equipment can act as a key enabler, most power companies simply use add-ons such as sensors, probes, meters, and thermal imaging equipment to collect real-time data, and third-party AI software to process this data. This practice is commonly known in the industry as predictive maintenance.

AI-based predictive maintenance algorithms and software can detect faults and repair them before an asset breaks down. Industrial automation companies such as Emerson, ABB, and GE are leaders in providing predictive maintenance solutions such as vibration monitoring, infrared thermography, and lubricant oil analysis.

Some of the most exciting AI developments in power come in the field of nuclear energy, which attracts attention due to its high energy density and low emissions profile. Applications of AI in nuclear fission revolve around predictive maintenance of equipment and the safer disposal of radioactive waste. However, AI has the most potential to enact change in nuclear fusion. The emerging energy source is largely still in the research & development phase, with few industry experts expecting the availability of commercial fusion reactors before 2030. Research groups often share fusion reactors, limiting the time available for experiments. AI can speed up the R&D timeline through modelling and simulations. In February 2022, DeepMind collaborated with the Swiss Plasma Center (SPC) to develop a deep reinforcement learning system for tokamak nuclear fusion simulations.

The potential for generative AI to disrupt the power industry is large, despite there currently being no prominent examples of its use.

The most natural application of generative AI in the power industry is facilitating the interpretation of the massive amounts of data coming from predictive maintenance equipment. AI algorithms are already being used to analyse this data, but generative AI capabilities like large language models can help reduce the barriers to understanding the technology for staff that lack the required skills to use existing AI systems. In July 2023, ABB and Microsoft announced a partnership to integrate Copilot, Microsofts large language model, into Ability GenixABBs IoT, analytics, and AI platform.

Unsurprisingly, generative AI has the most value at the edge of the power value chain, using natural language processing to help users make more optimized decisions about their energy consumption. Smart home energy systems currently use AI and machine learning algorithms to analyse energy usage patterns. Although no prominent generative AI models exist specifically for use in managing energy usage, the technology can reduce the barriers to educating end users on energy logistics as well as creating effective strategies for energy consumption. In this way, homeowners can reduce consumption and save money on their energy bills.

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Artificial intelligence in power: an old dog with new tricks - Power Technology