Artificial intelligence technology, such as ChatGPT, has been found to be as accurate as a developing practitioner in clinical decision-making and diagnosis, according to a study by Massachusetts researchers. The technology was 72% accurate in overall decision-making and 77% accurate in making final diagnoses, with no gender or severity bias observed. While it was less successful in differential diagnosis, the researchers believe AI could be valuable in relieving the burden on emergency departments and assisting with triage.
A study led by Mass General Brigham found that ChatGPT, an AI chatbot, demonstrated 72% accuracy in clinical decision-making, suggesting that language models have the potential to support clinical decision-making in medicine with impressive accuracy.
Kaiser Permanente is using augmented intelligence (AI) to improve patient care, with programs such as the Advanced Alert Monitor (AAM) that identifies high-risk patients, as well as AI systems that declutter physicians' inboxes and analyze medical images for potential risks. These AI-driven applications have proven to be effective in preventing deaths and reducing readmissions, demonstrating the value of integrating AI into healthcare.
Artificial intelligence (AI) has the potential to revolutionize healthcare by improving disease detection and diagnosis, enhancing healthcare systems, and benefiting health care providers, but it also presents challenges that must be addressed, such as developing robust and reliable AI models and ensuring ethical and responsible use.
Artificial intelligence (AI) has the potential to greatly improve health care globally by expanding access to health services, according to Google's chief health officer, Karen DeSalvo. Through initiatives such as using AI to monitor search queries for potential self-harm, as well as developing low-cost ultrasound devices and automated screening for tuberculosis, AI can address health-care access gaps and improve patient outcomes.
Amsterdam UMC is leading a project to develop Natural Language Processing (NLP) techniques to tackle the challenges of using AI in clinical practice, particularly in dealing with unstructured patient data, while also addressing privacy concerns by creating synthetic patient records. The project aims to make AI tools more reliable and accessible for healthcare professionals in the Dutch health sector, while also ensuring fairness and removing discrimination in AI models.
UF Health in Jacksonville is using artificial intelligence to help doctors diagnose prostate cancer, allowing them to evaluate cases more quickly and accurately. The AI technology, provided by Paige Prostate, assists in distinguishing between benign and malignant tissue, enhancing doctors' abilities without replacing them.
Generative AI models like ChatGPT can produce personalized medical advice, but they often generate inaccurate information, raising concerns about their reliability and potential harm. However, as AI technology advances, it has the potential to complement doctor consultations and improve healthcare outcomes by providing thorough explanations and synthesizing multiple data sources. To ensure responsible progress, patient data security measures, regulatory frameworks, and extensive training for healthcare professionals are necessary.
Artificial intelligence (AI) is changing the field of cardiology, but it is not replacing cardiologists; instead, it is seen as a tool that can enhance efficiency and improve patient care, although it requires medical supervision and has limitations.
The accuracy of AI chatbots in diagnosing medical conditions may be an improvement over searching symptoms on the internet, but questions remain about how to integrate this technology into healthcare systems with appropriate safeguards and regulation.
Artificial intelligence (AI) in healthcare must adopt a more holistic approach that includes small data, such as lived experiences and social determinants of health, in order to address health disparities and biases in treatment plans.
Researchers at OSF HealthCare in Illinois have developed an artificial intelligence (AI) model that predicts a patient's risk of death within five to 90 days after admission to the hospital, with the aim of facilitating important end-of-life discussions between clinicians and patients. The AI model, tested on a dataset of over 75,000 patients, showed that those identified as more likely to die during their hospital stay had a mortality rate three times higher than the average. The model provides clinicians with a probability and an explanation of the patient's increased risk of death, prompting crucial conversations about end-of-life care.
Scientists at The Feinstein Institutes for Medical Research have been awarded $3.1 million to develop artificial intelligence and machine learning tools to monitor hospitalized patients and predict deterioration, aiming to improve patient outcomes.
Google Health's chief clinical officer, Michael Howell, discusses the advances in artificial intelligence (AI) that are transforming the field of medicine, emphasizing that AI should be seen as an assistive tool for healthcare professionals rather than a replacement for doctors. He highlights the significant improvements in AI models' ability to answer medical questions and provide patient care suggestions, but also acknowledges the challenges of avoiding AI gaslighting and hallucinations and protecting patient privacy and safety.
Doctors at Emory University conducted a study testing the accuracy of AI systems like Chat GPT, Bing Chat, and Web MD in diagnosing medical conditions, finding that Chat GPT correctly listed the appropriate diagnosis in its top three suggestions 95 percent of the time, while physicians were correct 95 percent of the time, suggesting that AI could potentially work alongside doctors to assist with initial diagnoses, but not replace them.
Major drugmakers are using artificial intelligence (AI) to accelerate drug development by quickly finding patients for clinical trials and reducing the number of participants needed, potentially saving millions of dollars. AI is increasingly playing a substantial role in human drug trials, with companies such as Amgen, Bayer, and Novartis using AI tools to scan vast amounts of medical data and identify suitable trial patients, significantly reducing the time and cost of recruitment. The use of AI in drug development is on the rise, with the US FDA receiving over 300 applications that incorporate AI or machine learning in drug development from 2016 through 2022.
