Applications of AI in Healthcare and Finance

About 119 million patients engage in digital and in-person healthcare-related activities (PYMNTs). Using this AI tool can be a game-changer. 🔽 Developed by JESS3 Design Studio, Connor Brennan, and Brian Solis, the GenAI Prism is a comprehensive mental model of generative AI startups, including ChatGPT and Jasper.ai. It provides valuable insights into turning visionary ideas into revolutionary content. Its design refracts the "light" of GenAI into manageable segments that guide users through the intricate process of leveraging AI. Each segment is organized as follows: Center > The initial idea for a prompt. Halo 1 > Balancing risk and reward. Halo 2 > Defining the outcome you are trying to accomplish: Augment, Create, Automate, Optimize, or Solve. Halo 3 > Determining the genre you can use to achieve your goals: Design, Flows, Conversational, Text, Video, and Sound. Halo 4-5 > Categorizing services and apps by capabilities, activities, and outcomes. Halo 6 > Interpreting the results: Iterative, Innovative, Exponential, or Experimental. Halo 7 > Evaluating what a given product achieved: Communicate, Grow, and/or Learn. These ultimately allow organizations to 🔷 Enhance creativity 🔷 Improve efficiency 🔷 Advance projects 💫 According to Brian, GenAI isn’t here to do the work of people or replace them, but to put AI in service of people and augment human potential. In healthcare and dental practices, GenAI has an especially promising outlook. 👉 Around 53% of people surveyed by VideaHealth are open to the use of AI in dentistry 👉 62% of dentists agreed that some operational tasks could be carried out by AI, with 35% having already implemented AI in their dental practice (http://Dentaly.org ) As more and more people accept and embrace AI, healthcare professionals can use it to ▶️ Increase efficiency in healthcare diagnoses ▶️ Optimize administrative workflow ▶️ Improve patient experience At Patient Prism , we’ve utilized AI to enhance practice growth and empower healthcare providers. Our integrated AI platform has helped healthcare companies and dental practices recover 30% of lost revenue opportunities and increased new patient appointments to up to 90% of new patient calls, increasing profits and preventing the loss of potential patients. AI is set to continue transforming the healthcare landscape and market. It’s time to use GenAI and boost outcomes. #GenAIPrism #artificialintelligence #healthcareinnovation Credit: JESS3 and Brian Solis

Healthcare systems are slowly developing generative AI use cases. This great STAT resource tracks publicly disclosed activity. Not surprisingly, ambient clinical note documentation is the most common application. Several systems (including mine) are harnessing generative AI to draft responses to patient messages. A few are using generative AI to identify missed diagnoses and care gaps and predict inpatient length of stays and mortality risk. I see considerable opportunities in two areas. 1. Summarizing patient records and referrals. Did you know physicians spend one-third of their EHR time on chart review? (doi:10.7326/M18-3684). 2. Helping clinicians better manage their In Boxes, which is a job in itself. (e.g., doi:10.1007/s11606-022-07766-0). As Benedict Evans recently wrote, "When we get a new tool, we start by forcing it to fit our existing ways of working, and then over time, we change the work to fit the new tool." So, how we use generative AI (and how we work) will undoubtedly shift over time. #healthcareai #healthcareinnovation #healthcareonlinkedin https://lnkd.in/gQkPkq9E

#Artificialintelligence is taking over #healthcare, yet its potential extends far beyond initial diagnostics. The recent FDA approval of AI-powered tool for sepsis diagnosis underscores a transformative shift, but this is just the beginning. Here’s why the impact of #AI is profound and what it means for the future: ↪ Enhanced Diagnostics: AI's ability to analyze multiple health parameters simultaneously has already improved sepsis detection, a notoriously complex challenge due to its rapid progression and severity. ↪ Systemic Transformation: Beyond diagnostics, AI is set to redefine treatment planning, chronic disease management, and surgical procedures. However, integration into existing healthcare frameworks is slow. AI is being applied in various capacities: ↪ Treatment Personalization: Leveraging patient data to tailor treatments enhances efficacy and patient outcomes. ↪ Chronic Management: Predictive models for diseases like diabetes or heart conditions offer proactive health management solutions. ↪ Surgical Precision: AI assists in surgeries, providing higher precision and potentially reducing human error. ↪ Workflow Integration: Despite these advancements, AI tools need seamless integration into daily medical practices to truly transform healthcare. What steps do you think are crucial for integrating AI into healthcare systems effectively? #FutureOfMedicine #HealthTech

The Future of Augmented Intelligence in Medicine. Here are some of the key ways that augmented intelligence could shape the future of medicine: Automated Diagnostics AI is getting incredibly good at analyzing medical images and detecting abnormalities and patterns that humans would miss. By automating tasks like screening X-rays or pathology slides, AI systems can assist doctors by flagging the most pressing cases that require further examination. Over time, AI diagnostics could become faster and more accurate than humans in certain applications. This could greatly benefit fields like radiology, ophthalmology, dermatology, and more. Intelligent Clinical Assistants Voice-enabled AI assistants will likely become standard partners for healthcare workers. Doctors could dictate patient notes to these assistants, ask medical questions to brush up on knowledge, enter orders and prescriptions, and request information from patient records. By automating documentation and administrative tasks, AI assistants could save doctors significant time and energy during long shifts. Smart Medical Devices AI embedded in medical devices could make procedures safer and more precise. For example, AI-guided robotic surgery systems are already helping doctors perform minimally invasive procedures. Endoscopes with AI capabilities could detect early signs of cancer during screening exams. Such smart devices that integrate AI into clinical care could greatly assist with early diagnosis and treatment. Personalized Medicine An AI system that can synthesize all of a patient's data - their medical history, genetics, lab tests, etc. - could provide customized treatment recommendations. This "precision medicine" approach accounts for each person's unique characteristics. AI may also uncover new personalized medicine insights as more biometric data from wearables gets incorporated. Improved Clinical Trials AI could optimize many aspects of drug development and clinical trials, such as patient selection, dosing, trial design, and more. It can also quickly analyze trial data to surface insights. By accelerating the pharmaceutical process, AI could lead to faster drug discovery. Smarter Hospital Operations Hospitals generate massive amounts of data that can be used to optimize workflows and processes. AI could improve scheduling, bed assignments, staffing allocation, supply chain management, and other operations. This could lead to better utilization of hospital resources. While there are valid concerns around AI like algorithmic bias and the black box problem, the healthcare industry is likely on the cusp of major transformations driven by augmented intelligence. With the right governance and oversight, AI could make medicine faster, more personalized, and potentially more accessible. The future looks promising as long as we build and deploy these technologies thoughtfully. #heathcare #innnovation #ai #medical