HIMSS 2023: Disruptive Ai in Healthcare
Authors: Brynne Rozell DO, Jessa Deckwa BS, and Zain Khalpey, MD, PhD
We at Khalpey AI Lab are working to advance and improve the use of AI technologies in healthcare. We believe strongly that artificial intelligence is an important tool to advance the healthcare industry and will bring it to new heights in the future. Starting with simple managerial tasks and working toward fully functional AI-based physicians is the path we envision for AI in healthcare. We see AI as an exciting and useful development to improve how we care for our patients and to drive down healthcare costs.
This year, at HIMSS 2023 Chicago, Dr. Khalpey presented “Disruptive AI in Healthcare.”
The mission of the Healthcare Information and Management Systems Society (HIMSS) is to reform the global health ecosystem through the power of information and technology. We presented the possibility of an AI Driven Hospital and discussed how the integration of Ai has failed in healthcare and is not currently end user friendly. Dr. Khalpey focused on three key categories of Ai integration: applied, translational and basic science and research applications which could improve the integration of Ai into healthcare to be impactful and truly change patient lives.
Applied Ai-powered healthcare will empower providers by processing patient records, genetic information, and real-time data, and make more informed decisions using AI algorithms. AI has already been employed in various healthcare settings, including early cancer detection, remote patient monitoring, and management of chronic diseases. AI-powered healthcare will empower providers to make better decisions, improving patient outcomes and revolutionizing the industry. This aligns with the HIMSS Accelerate initiative which connects global health ecosystems to insights from peers and thought leaders, professional development tools, networking opportunities. During the presentation we discussed the opportunities for Ai integration into the operating room and intensive care units to augment a physician’s medical decision making and key in on the abnormal data points for better patient care.
Translational Ai can transform healthcare by enhancing diagnostics, revolutionizing treatment plans, and AI algorithms are disrupting translational healthcare. AI-powered imaging and predictive analytics can rapidly process complex data to aid in diagnostics, optimize treatment, and reduce healthcare costs. By analyzing medical images, waveforms, and other data, AI algorithms can quickly identify abnormalities, suggest possible interventions, and predict patient outcomes.
In Basic science and research Ai processing vast amounts of data on chemical compounds and biological targets, AI algorithms are accelerating Discovery and Development, identifying new targets for personalized therapeutics, and analyzing chemical structure. This aligns with the HIMSS Accelerate initiative which connects global health ecosystems to insights from peers and thought leaders, professional development tools, networking opportunities. During the presentation we discussed the opportunities for Ai integration into the operating room and into the bedside to augment a physician’s medical decision making and key in on the abnormal data points for better patient care.
Our vision for the next generation of Ai tools:
Short-term (1-3 years):
Focus on applied clinical healthcare by integrating AI algorithms into existing healthcare systems, enhancing early detection, and supporting personalized treatment plans.
Mid-term (3-5 years):
Expand AI applications in translational healthcare to improve diagnostics, optimize treatment options, and reduce costs.
Long-term (5-10 years):
Foster AI-driven innovation in basic research, accelerating drug discovery and development, and advancing personalized therapeutics.
In order to achieve this vision, we would need to form partnerships with industry to engage healthcare institutions, universities, and research centers in the development and implementation of AI-driven solutions. By establishing strategic partnerships with technology companies, pharmaceutical firms, and healthcare providers we can ensure cutting-edge solutions are developed and deployed effectively. We also need to encourage cross-disciplinary collaboration to accelerate AI integration and drive innovation in healthcare. We would also need to work closely with government agencies to develop and enforce clear guidelines and regulations for AI use in healthcare. This would ensure the privacy and security of patient data, adhering to global best practices and local regulations. Implementation of ethical AI practices guarantee fairness, transparency, and accountability in AI-driven healthcare solutions. Most importantly we need to develop comprehensive training programs for healthcare providers, ensuring they are well-equipped to harness the power of AI. Integrate AI-focused curricula into medical and nursing schools to prepare future healthcare professionals for a technology-driven industry. Encourage continuous professional development and upskilling to keep healthcare providers updated on the latest AI advancements.
In addition to sharing his vision for building an AI Ecosystem in healthcare, Dr. Khalpey also unveiled the latest innovation in medical technology: Kai the AI Physician Chatbot.
AI search engines have the potential to transform the way that both physicians and patients access important healthcare information. By leveraging the power of AI strategies like machine learning and natural language processing, AI search engines can quickly and accurately sift through vast amounts of medical information and provide relevant results that are tailored to the user’s needs. However, the effectiveness of AI search engines depends on their ability to provide trustworthy and reliable information. In the context of healthcare, the consequences of inaccurate or biased information can be severe and potentially life-threatening. Therefore, it is essential to establish strategies to ensure that AI search engines are trustworthy and that their results can be trusted by both physicians and patients.
As clinicians ourselves, our team understands the importance of accessing reliable and accurate information for patients. Medical research produces an enormous amount of data and information. This vast amount of information can be cumbersome and inefficient to navigate, oftentimes requiring advanced knowledge to understand and assimilate the complex topics and technical jargon.
This is why we spearheaded Kai, the first of its kind AI physician. This AI medical search engine can sift through vast amounts of information to provide healthcare professionals and patients with the most relevant and up-to-date medical information. This cutting-edge tool is powered by ChatGPT, a powerful natural language processing platform. Kai is designed to cater to various aspects of healthcare depending on your role and needs. Choose from three specialized models: Kai Patient, Kai Clinician, and Kai Scientist.
Designed for patients seeking general information about heart surgery, including what to expect, how to prepare, and understanding risks and benefits. Kai Patient provides reliable, personalized information based on your condition and preferences.
Kai Clinician (beta):
Tailored for healthcare professionals seeking clinical information related to medical and surgical diseases, such as diagnosis, treatment, guidelines, and best practices. Access the latest evidence and expert opinions from reputable sources and peers with Kai Clinician.
Kai Scientist (beta):
Crafted for researchers inquiring about scientific or translational questions in health sciences, such as literature reviews, data analysis, grant writing, and collaboration. Kai Scientist assists in finding relevant, high-quality information and resources for your research projects.
This Kai tool is only the beginning of creating an Ai-ecosystem in healthcare, complete with Ai-pocket tools for healthcare professionals in every field. Read about more of our work and our vision for an Ai-augmented precision healthcare future at the following links: